JPS5925427B2 - Noise removal circuit - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION To remove noise contained in an input signal, such as a video signal obtained from a VTR, a noise removal circuit having a low-pass filter or a high-pass filter is generally used.

For example, as shown in FIG. 1, a video signal Si supplied to a terminal 1 is supplied to a low-pass filter 2 and a high-pass filter 3, respectively, and the output obtained from the high-pass filter 3 is further transmitted to a second filter.
As shown by curve 1 in the figure, after obtaining an output signal which is supplied to a non-linear circuit 4 having an input/output characteristic having a dead zone Ta to remove noise existing within the dead zone Ta, the output signal is synthesized with the output of the low-pass filter 2 described above. 5, and an output video signal 50 containing no noise signal is obtained from a terminal 6.

This noise removal circuit aims to improve image quality by removing noise components that exist in the high frequency range, but when filter circuits such as low-pass filters and high-pass filters are used in this way, the following It has the following drawbacks.

That is, in this conventional circuit, in addition to insufficient separation of the signal component and noise component in the video signal Si, the signal component of the output of the high-pass filter 3 is subjected to large distortion in the nonlinear circuit 4, so that the reproduced image is Fine luminance changes in areas where luminance changes are small, such as the background, disappear, and as a result, scale-like patterns occur in images corresponding to areas where luminance changes are gradual.

On the other hand, if the brightness changes are steep, smear occurs and the sharpness of the image deteriorates. In order to remove noise without suffering much image degradation, that is, to effectively remove noise in signal components, it is necessary to better separate the signal component and noise component, and then perform signal manipulation to remove the noise. In addition, when manipulating the signal, it is sufficient that the signal subjected to distortion is not so noticeable from the human visual characteristics. In order to satisfy each of these conditions, orthogonal transformation may be used.

The idea of using orthogonal transform to remove noise and improve image quality deterioration was immediately proposed by the applicant, but the present invention deals with a noise removal circuit that uses this orthogonal transform. Furthermore, as will be described later, a part of the inversely transformed output is used as an input signal to an orthogonal transform circuit, thereby eliminating noise particularly on the low frequency side and further improving the image quality. A noise removal circuit using orthogonal transform according to the present invention will be described below with reference to the drawings, but first, a few words about orthogonal transform will be described first.

Now, if we represent the block of the video signal sequence that is the input signal as X, the block of the output signal sequence as Y, the orthogonal transformation matrix as A, and the inverse transformation matrix as B, then (
(AT is a transposed array) Therefore, when the input signal is orthogonally transformed, the inverse transform output is: Therefore, the transform coefficient, that is, the orthogonal transform output Y becomes a linear combination of the row vector and the input signal.

By the way, in the present invention, orthogonal transforms such as Warschu, Hadamard, and Barr can be used, but in this example, the characteristics of the television signal can be well extracted, and the inverse transform can be performed using the same procedure as the transform. Let us exemplify the case of using the Hadamard transformation, which has the characteristics of being able to perform the following.

FIG. 3 shows an example of a noise removal circuit using orthogonal transform that has already been proposed by the applicant, and this example shows the case of one-dimensional orthogonal transform.

That is, as shown in FIG. 4, for a plurality of consecutive unit areas (one picture element in terms of an image, and the numbers correspond to this) in a video signal in a certain horizontal scanning section, these multiple unit areas are This is a case where signals corresponding to a unit area are orthogonally transformed as a set. The video signal Si supplied to the terminal 11 is supplied to a parallelization circuit 12 to obtain a plurality of temporally synchronized video signals.

The parallelization circuit 12 is composed of a plurality of delay lines connected in series, and the number of delay lines to be used is determined from the matrix configuration of the orthogonal transformation circuit, which will be described later. In this example, three delay lines 12a to 12c are connected in series. Note that the delay amounts τ are both selected to be equal, and in this example are about 100 ns.

This delay amount τ is determined by the sampling frequency Fc required to sample the entire band of the video signal Si,
For example, if the entire band of the video signal Si is about 4.5 MHz, the sampling frequency is about 10 MHz, so in that case, the delay amount τ is selected to be 100 ns. By the way, if the video signal supplied to the terminal 11, that is, the non-delayed output, is denoted as Si4, a plurality of delayed outputs Sil~ obtained from the delay lines 12a~12c for parallelization.
Si3 is supplied to the orthogonal transform circuit 20, respectively.

The orthogonal transform circuit 20 employs Hadamard transform as described above. For convenience of explanation, this example uses a fourth-order Hadamard transformation matrix.

Therefore, the matrix structure is as shown in equation (8) below. In order to realize this fourth-order Hadamard transformation matrix H4, it is sufficient to configure it as shown in FIG.

The fourth-order Hadamard transform circuit 20 has four row lines 11 to 14 and four column lines m1 to M4, respectively, as shown in the figure.
1 to 14 are further branched into two row lines in order to extract the positive and negative signals supplied thereto separately, and one of the row lines is provided with a phase inversion circuit 15, respectively.

A plurality of attenuators 1 are provided between the plurality of row lines and column lines so as to satisfy the matrix condition of equation (8).
3 are connected between the desired lines. Therefore, if the outputs Sil to Si4 obtained by the parallel circuit 12 are supplied to the terminals 21a to 21d of the plurality of row lines 11 to 14, respectively, the desired outputs will be output from the terminals 22a to 22d of the plurality of column lines m1 to M4, respectively. Orthogonal transformation outputs SO1 to SO4 are obtained.

These orthogonal transformation outputs are expressed by the following equation. Next, let us examine the properties of the orthogonal transform outputs SO1 to SO4 obtained in this way.

Since the power spectrum of the video signal contains many low frequency components as shown in FIG. 9, there are many parts that change smoothly.

Furthermore, as is well known, the high frequency components of the video signal correspond to the limbal portion of the image, and the low frequency components correspond to positions in the image where the brightness does not change much. Therefore, among the orthogonal transform outputs, the low-order transform outputs, ie, SO in this example, have a strong tendency to contain many low frequency components, whereas the high-order orthogonal transform outputs, ie, SO2 to SO4, have a strong tendency to contain many low frequency components. tends to contain high frequency components. This tendency is strong in the case of high-order transformation matrices such as 8th and 16th orders.

In other words, by orthogonally transforming a video signal, this video signal is concentrated in the low-order orthogonal transform output, and the higher the order, the less it appears in the orthogonal transform output. It means something. On the other hand, noise contained in a video signal obtained from the output of a VTR or the like is distributed over substantially the entire band and is considered to be random noise.

Therefore, when a video signal with such noise is orthogonally transformed, the noise components will be distributed with approximately uniform amplitude in each orthogonal transform output. Orthogonal transform output lζ The S/N is good, and the noise component is dominant in the high-order orthogonal transform output, so its S/N is
deteriorates. What can be said from these facts is that when the level of the orthogonal transform output is high, it can be regarded as a video signal component.

On the other hand, if the level of the orthogonal transform output is small, it may be regarded as a noise component. Moreover, as mentioned above, the S/N deteriorates in high frequency components, but since the human visual characteristics for these high frequency components generally deteriorate,
Even if the reproducibility in the high frequency region during reproduction is poor, it does not have much influence on the reproduced image. From the above, when the orthogonal transform output is at a low level that is approximately determined by the frequency spectrum of the noise, the configuration is such that it is regarded as a noise component and removed.

Therefore, a non-linear circuit 16 is provided at the subsequent stage of the orthogonal transform circuit 20, and by supplying the respective orthogonal transform outputs SO1 to SO4 to this non-linear circuit 16, the noise present in the dead zone 7a shown in FIG. 2 is removed. It was designed to do so.

In this example, other outputs SO1 except the orthogonal transformation output SO1
Nonlinear circuits 16a to 16c are installed on the transmission paths of 2 to SO4, respectively.
are provided to remove noise contained in the respective signals SO2 to SO4.

Note that the reason why the nonlinear circuit 16 is not interposed in the first orthogonal transformation output SO1 is to prevent waveform distortion etc. from occurring in this output SO1, which greatly affects the reproduced image. Sasa 2
A specific circuit example of the nonlinear circuit 16 having input/output characteristics as shown in the figure is shown in FIG.

Since the nonlinear circuit 16 described below is conventionally well-known, its outline will be explained as follows: The orthogonal conversion output is passed through an amplifier 21 for buffering, and a circuit 22A and a circuit 22A that apply DC bias in a desired direction, respectively. 22B. One circuit 22A biases the signal in the positive direction as shown, and therefore the other circuit 22B biases the signal in the negative direction. The outputs obtained from these circuits 22A and 22B are sent to the half-wave rectifier circuit 23.
After being supplied to A and 23B, it is supplied to the combiner 24.

Therefore, the synthesized output obtained from the synthesizer 24 is below the desired level, that is, from which noise components existing within the dead zone 7a in FIG. 2 are removed. Note that the nonlinear circuit applicable to the present invention is not limited to the above example, and may of course be a nonlinear circuit having input/output characteristics as shown in FIG. 7, for example.

In this case, the configuration is as shown in FIG. In the figure, 25A is an amplifier for the buffer, 26 is a double-wave rectifier circuit, and 27 is a comparison circuit, in which the rectified output is compared with a reference value. 27a is a reference value (voltage) supply terminal.

When the rectified output is larger than the reference value, the switch circuit 28 connected in parallel to the signal transmission path is opened (
OFF), otherwise it is ON. Therefore, the input/output characteristics shown in FIG. 6 can be obtained, so that the desired noise removal can be achieved. In addition, 25B
indicates a buffer amplifier. In this way, if the orthogonal transform outputs SO2 to SO4 are supplied, respectively, with the desired nonlinear circuits 16a to 16c interposed in the respective transmission paths,
Outputs obtained by removing noise components contained in high-order orthogonal transform outputs are obtained from each nonlinear circuit. These outputs and the above-mentioned orthogonal transform output SO1 are respectively supplied to the inverse transform circuit 30. In the case of the Hadamard transform, the inverse transform can also be performed using the same procedure as the transform circuit, so the inverse transform circuit 30 also has exactly the same configuration as the orthogonal transform circuit 20 described above.

Therefore, the above-mentioned orthogonal transformation output S is applied to the terminals 21a to 21d.
By supplying Ol to SO4, respectively, the inversely transformed outputs Si{ to Sil from which noise has been removed can be obtained from the terminals 22a to 22d, respectively. Therefore, this inverse transformation output Sill
By supplying -Si{ to the serialization circuit 31 consisting of a delay line, an output signal SO from which noise components have been removed can be obtained from the terminal 32. Serialization circuit 3
1 is composed of three series-connected delay lines 31a to 31c similar to the parallel circuit 12, and the delay amount of each is selected to be 100 ns as described above.

Then, by supplying the above-mentioned inversely converted outputs to desired terminals of these delay lines 31a to 31c, a desired output signal in which the video signal corresponding to the unit area is made continuous can be obtained. It should be noted that since Hadamard transform can perform orthogonal transform and inverse transform using the same procedure as described repeatedly, the same matrix configuration can be used both as an orthogonal transform circuit and as an inverse transform circuit.

FIG. 10 shows an example of a case where a conversion circuit is shared, and in this example, a conversion circuit 29 configured similarly to that shown in FIG.
are provided, and input signals Sil to Si4 to be orthogonally transformed are provided here.
and the orthogonal transform outputs SO1 to SO4 to be inversely transformed are supplied in a time-division manner.

Reference numeral 34 indicates a time division circuit composed of a kind of switching circuit. First, the input signals Sil to Si4 are taken out and orthogonally transformed, and then supplied to the nonlinear circuit 16 via the signal separation circuit 35, which will be described later. Orthogonal transform outputs SO, ~SO4 from which noise signals have been removed are obtained.

Next, if these orthogonal transformation outputs SOl to Sn4 are supplied to the transformation circuit 29 via the time division circuit 34, inverse transformation outputs Si'1 to Si'1 to Si' can be obtained in the same way, and these are serialized through the separation circuit 35. If the signal is supplied to the circuit 31, the desired output signal SO will be obtained from the terminal 32. The separation circuit 35 thus has the function of supplying only the inversely converted output to the serialization circuit 31, and therefore the time division circuit 34 and the separation circuit 35 operate in conjunction with each other.

Note that a delay circuit 36 provided at a subsequent stage of the nonlinear circuit 16
is for timing adjustment for time division.

In this way, if orthogonal transformation and its inverse transformation are used as the signal transformation method, the signal relationship between the orthogonal transformation and the inverse transformation will be exactly the same.

Therefore, it is possible to very easily remove the deterioration of the reproduced image due to the mismatch in amplitude, phase characteristics, etc. between the respective filters, which occurs when a low-pass filter or a high-pass filter is used. In addition, as mentioned above, the frequency band from which noise is removed is a high-frequency component that does not particularly affect human visual characteristics, so even if the noise is removed, the reproduced image will not be affected much. . By the way, in a noise removal circuit using orthogonal transform as shown in FIG.
Let us briefly consider the signal content and time relationship between i4 and the inverse transformation output Sil-Si:. For convenience of explanation, if the signals Sil to Si4 and Siτ to Sil are illustrated as shown in FIG. 11 by taking only their subscripts, orthogonal transformation is performed by treating four consecutive unit areas parallelized in time as one set. Therefore, the time points T1 to T2 to be orthogonally transformed and the input signal to be transformed have the relationship shown in A in the figure, and the interval of transformation is one picture element, that is, τ. Therefore, the time from obtaining the orthogonal transform output to obtaining the inverse transform output is now +
If τ is assumed, the relationship between the inverse transform outputs will be as shown in FIG.
To make it easier to understand the relationship between the inverse conversion output and the input signal,
If the inverse transformation output is further delayed by +τ so that the time difference between the two corresponds to one picture element, the time relationship between the two becomes A in the same figure.
and C.

The following explanation will be based on this temporal relationship, but although the details of the signal configuration used for orthogonal transformation change from moment to moment, in this case, the new content of one picture element is the signal to be converted each time. The rest are the signals used as the signals to be converted in the previous conversion. For example, the converted signal at time T2 is the latest signal Si5
and signals Si2 to Si4 corresponding to three picture elements, of which signals Si2 to Si4 are the signals at the previous conversion (T1).
It is used in

Therefore, if noise is included in the signals Si2 to Si4, they will be used as transformed signals for a total of three orthogonal transformation operations while containing this noise. On the other hand, among the inversely transformed outputs at the time actuality (=T2), the outputs Si6 to S
ij is the same as the signal content of signals Si2 to Si4 at time T2. However, the conversion output Si! ~Sil has undergone noise processing, so the proportion of noise mixed in is small, but the information content is the same. Therefore, when performing orthogonal transformation processing on an input signal as shown in FIG. Instead of Si4, the outputs Si~Sij are used, and at time T3, the signal Si
3~Si5 instead of output Si〈~Si≦(of which Si!3
and Sil (output obtained by the above operation) are supplied to the orthogonal transform circuit in the same manner and subjected to the transform process. Compared to the case of converting a signal containing noise, it is possible to remove noise. It is easy to understand that even more can be achieved. Therefore, in the present invention, a part of the input signal to be orthogonally transformed is replaced with a part of the output that has been subjected to the inverse transform process to perform the transform process, that is, by applying feedback, the noise is reduced. It is designed to eliminate noise, especially in the low range.

The number of inverse transform outputs to be fed back as input signals
．． m is a positive number of 2 or more) and the delay amount τ of the circuit, and now the delay amount is set to N (N-nτ, n≧1, τ is a unit delay amount, so it is set as τ-1). In the one-dimensional case, the maximum amount of feedback can be achieved, and therefore the orthogonal transformation circuit 20
The number Y of original input signals supplied to is.

If applied to the embodiment shown in FIG. 3 having the relationship shown in FIG. 11, M=4 and N-1, so the number X of inversely transformed outputs that can be fed back is three at most. Therefore, it is sufficient to simply supply the input signal Sl itself to the orthogonal transformation circuit 20, and therefore the parallelization circuit 12 can be omitted in this example. 12th
The noise removal circuit according to the present invention will be described in detail with reference to the drawings, and in this example, an example will be described in which each of the conditions described above for the embodiment of FIG. 3 is applied.

The input signal S1 supplied to the terminal 11 is input to the orthogonal transform circuit 20.
The plurality of orthogonal transform outputs are supplied to the inverse transform circuit 30 via the corresponding nonlinear circuits 16a to 16c.

Here, the width Δw of the dead zone 7a of the nonlinear circuits 16a to 16c
can be kept constant, but it is also possible to vary it depending on whether the noise component contained in the video signal Si is large or small.

The embodiment deals with the latter case, and the explanation will be given later. Among the inverse transform outputs, the outputs excluding the oldest output in terms of time are fed back to the orthogonal transform circuit 20 as input signals, but the input signal currently supplied to the terminal 21a of the orthogonal transform circuit 20 is the newest input. signal, and similarly the inverse conversion circuit 30
In this case, if the transformed output obtained at the terminal 22a is the latest information, the latest transformed output obtained at the terminal 22a is fed back to the terminal 21b of the orthogonal transformation circuit 20.

Similarly, the output of the terminal 22b is transferred to the terminal 21c, and the output of the terminal 22b is transferred to the terminal 21c.
The outputs of the terminals c are fed back to the respective terminals 21d. Note that the delay circuits 37A to 37C provided in the feedback path are for adjusting the amount of delay N mentioned above, and in this example, the time required from the orthogonal transform output to the feedback is the time corresponding to one pixel. The delay time is chosen so that

Therefore, if it is assumed that the signals Sil to Si4 shown in FIG. 13A are input, the input/output relationship will become as shown in FIG. 13A and B after undergoing several conversions.

In the figure, the number "D" attached to the number indicating the signal indicates the number of times the conversion process is performed, and the same information is fed back three times, so as the conversion process progresses, signals with less noise are sequentially orthogonally transformed. become. Therefore, noise can be removed more effectively than when signal processing is performed without feedback. FIG. 14 shows the amplitude-frequency characteristic curve of the noise contained in the input video signal Si, where the frequency is F.

is the springing frequency and shows the case where Fc=10MHz. As mentioned above, noise in the input video signal Si is uniformly distributed over the entire band as shown by the curve 45 in the same figure, but when the noise processing shown in FIG.
6, it becomes possible to significantly remove noise that exists particularly on the high frequency side. However, when signal processing is performed by applying feedback as in the present invention, the noise is further reduced as shown by a curve 47, and in this case, it is also possible to effectively remove noise particularly on the low frequency side. The inversely converted outputs obtained as described above pass through level adjustment circuits 38A to 38D, respectively.
The signal is supplied to the serialization circuit 31, so that the desired video signal SO can be obtained at the terminal 32.

Note that the level adjustment circuits 38A to 38D are provided in order to reduce the image distortion by lowering the level of the part where the image distortion is particularly noticeable in advance. I will omit the detailed explanation, but as shown in Figure 4,
In the case of two unit areas, the unit areas existing on both sides of the unit area correspond to the latest information and the oldest information at the time of orthogonal transformation in the case of a fourth-order Hadamard transform.

Therefore, it is only necessary to lower the level of the converted outputs Sir and Si of these information in advance. In this example, by lowering the respective levels L1 and L4 to +, even if the distortion is distributed throughout, the distortion in the signal region appears to be small, and image deterioration can be prevented. By the way, in the system diagram shown in FIG. 12, the width ΔW of the dead zone 7a in the nonlinear circuit 16 can be varied by the following configuration.

In this example, a noise component existing at a black level during a no-signal period of a video signal, for example, a vertical retrace period, is detected, and gate circuits 41a to 41e are provided on the transmission path of the orthogonal transform output. and orthogonal transform outputs are supplied to each of them.

On the other hand, 42 indicates a gate signal forming circuit, and a gate signal formed based on the input video signal Si is supplied to the plurality of gate circuits 41a to 41c described above, and black level noise components in the vertical retrace period are extracted. . The extracted noise components are supplied to circuits 43a to 43c comprising a rectifier circuit and a low-pass filter at the subsequent stage, and the power of the noise components is determined.

The signal representing this power is supplied as a width control signal of the dead zone 7a in the corresponding nonlinear circuit 16. For example, when there are many noise components, this power output becomes large. Control may be performed by changing the bias of the nonlinear element to widen the width Δw of the dead zone 7a, and by doing so, the noise component in the video signal can be effectively removed. It should be noted that it is not necessary to particularly use electric power as the width control signal, and it is sufficient to use a circuit configured to obtain an output according to fluctuations in the noise component.

As explained above, in the present invention, noise is removed by orthogonal transformation, so in addition to being able to remove noise more effectively than in the past, in particular, in the present invention, a part of the inverse transform output is orthogonally transformed. Since it is fed back to the conversion circuit 20 and used as an input signal of this circuit 20, a signal with less noise component mixed in becomes the input signal, and therefore an inverse conversion output free of noise components can be obtained. Therefore, noise can be reduced compared to the case of FIG. 3, and especially in this case, noise can be removed even to the low frequency side of the signal.
It has the feature of being able to reproduce high-quality images. In the embodiment of the main part shown in FIG. 16, the delay amount N of the circuit is 2τ. A video signal and a signal delayed by τ are supplied.

48 indicates a delay circuit.

Since the other circuit configurations are the same as those described above, a description thereof will be omitted, but the same effects as described above can be achieved in this embodiment as well. In the above-described embodiment, noise is removed using a one-dimensional fourth-order Hadamard transform, but the selection and combination of dimensions and orders are arbitrary.

It goes without saying that when a Hadamard transform of a higher order is used, noise components can be removed more reliably down to the lower frequency range.

[Brief explanation of drawings]

FIG. 1 is a system diagram showing an example of a conventional noise removal circuit used to explain the present invention, FIGS. 2 and 7 are input/output characteristic curve diagrams used in the Fufu nonlinear circuit, and FIG. 3 is a diagram of the present invention. FIG. 4 is a system diagram showing an example of a noise removal circuit using orthogonal transformation to provide an explanation of FIG. 4 is a diagram showing an example of a video signal to be orthogonally transformed;
Fig. 5 is a circuit diagram showing an example of an orthogonal conversion circuit, Figs. 6 and 8 are connection diagrams showing an example of a nonlinear circuit, Fig. 9 is a curve diagram showing the power spectrum of a video signal, and Fig. 10 is a circuit diagram showing an example of a nonlinear circuit. 3
11 and 13 are diagrams for explaining the present invention. FIG. 12 is a system diagram showing an example of the noise removal circuit according to the present invention, and FIGS. 14 and 15 are system diagrams showing other embodiments. The figure is a curve diagram for explaining the operation, and FIG. 16 is a system diagram of the main parts showing still another example of the present invention. 12 is a parallelization circuit, 20 is an orthogonal conversion circuit, 16 is a nonlinear circuit, 30 is an inverse conversion circuit, 31 is a serialization circuit, Si is a video signal that is an input signal, SO is a video signal from which noise has been removed, Sil... −・・・・・・ is a synchronized video signal,
Si{...... is the inverse transformation output.

Claims (1)

[Claims] 1. Supplying the input signal to an orthogonal transform circuit to perform orthogonal transformation, supplying a plurality of orthogonally transformed transform outputs to a nonlinear circuit, and then supplying them to an inverse transform circuit to obtain an inverse transform output from which noise has been removed. , a noise removal circuit characterized in that a part of the inverse transform output is used as an input signal of the orthogonal transform circuit.