JPH0628413B2 - Defect detection device for solid-state image sensor - Google Patents

Description

The present invention relates to a defect detection apparatus for a solid-state image sensor, and is applied to a case where a quality of a product is judged when the solid-state image sensor used in a video camera is manufactured. And is suitable.

[Background technology and its problems]

Since this type of solid-state image sensor has a large number of pixels formed on a plane lattice, it is practically difficult to obtain a solid-state image sensor having uniform characteristics over the entire light-receiving surface of the image sensor during manufacturing. The photoelectric conversion output obtained from the pixels arranged in sequence contains various noise components.

That is, when the photoelectric conversion output RD is detected for one horizontal section, as shown in FIG. 2 (A), the photoelectric conversion output RD is, firstly, an average signal when the solid-state imaging device is horizontally scanned. It has a shading component SH whose level gradually changes. This shading component SH is generated on the basis of aperture irregularity, conversion irregularity, etching irregularity, filter irregularity, etc. of each pixel and has a relatively low frequency.

Secondly, the photoelectric conversion output RD has a noise component K0 generated based on the unevenness between pixels. This noise component K0 has a relatively high frequency, and its fluctuation range is relatively large.

The above is a phenomenon that can be seen in a solid-state image sensor that does not include a defective pixel. However, if there is a defective pixel, the photoelectric conversion output RD is a white defect that rises in a pulse shape at a position corresponding to the defect WD or black defect BD will occur.

As described above, the detection data RD including various fluctuation components
Conventionally, a method of extracting the detection data RD using a spatial filter has been used in order to detect defects WD and BD based on pixel defects from among the above and detect the defective pixels. However, according to this method, it is necessary to set the size of the spatial filter and the weighting function so as to be applied to the size, type or frequency characteristic of the defect to be detected, but in practice it is set to the optimum value. In many cases, it is extremely difficult to design a spatial filter having an optimum frequency characteristic when detecting a defect from the detection data RD based on the frequency characteristic. It is practically difficult to implement with a x3 or a 5x5 filter.

Further, according to the conventional defect detection method, when the defect is determined by comparing the output obtained from the spatial filter to which the detection data RD is supplied with the reference value in the comparator, the defect aggregation state and If the signal level of the detection data RD changes when the output level changes, it is impossible to estimate the true data obtained from the defective pixel, which makes it difficult to automatically determine the defective pixel.

For example, the set of Laplacian -1-1-1 -1 8-1 -1-1-1 for defects changes as shown in FIG.

Further, according to the conventional defect detection method, when performing the defect detection processing using the spatial filter, it is not possible to obtain the determination result for the pixels in the area of the outer peripheral edge of the solid-state image sensor. Incidentally, in this conventional defect detection method, it is usual that the range of spatial filtering is wide and the filtering process is performed a plurality of times, which inevitably causes a blank area at the peripheral edge.

For example, when a 3 × 3 space filter is used for the defect detection data RD, the calculation cannot be performed for one bit of pixels in the outer peripheral area as shown in FIG.

[Object of the Invention]

The present invention has been made in consideration of the above points, and in obtaining a shaded extraction output from an image signal, a defect removal filter is operated digitally to form a blank area at the peripheral portion of the solid-state image sensor. It is intended to effectively solve the problem that a defect detection process cannot be performed for a certain pixel.

[Outline of Invention]

In order to achieve such an object, in the present invention, the first shading data is extracted by subjecting the detection data obtained from the solid-state imaging device to digital arithmetic processing, and the extracted first shading data is extracted. Of the data of the second pixel group arranged inside the first pixel group in the area of the outer peripheral edge of the solid-state image sensor,
Is interpolated as the second shading data corresponding to the pixel group, and the interpolation output data is subtracted from the detection data to obtain a defect detection signal which is a defect signal included in the detection data.

〔Example〕

An embodiment of the present invention will be described in detail below with reference to the drawings. About FIG. 1, 1 is a solid-state image sensor, for example, CCD (charge)
A large number of pixels, which are coupled devices, are arranged on a plane lattice in the H direction and the V direction, and the irradiation light from the light source 2 is photoelectrically converted. The photoelectric conversion output of each pixel is
The horizontal clock signal SH and the vertical clock signal SV generated by the clock driver 3 are sequentially scanned by 1H at a time and input as time-serial detection data RD to the analog-digital conversion circuit 5 through the input circuit 4. After being converted into a digital signal, it is input to the picture memory 7 of the shielding extraction circuit 6. The picture memory 7 executes the synchronous addition operation for each pixel by using the accumulator 8 every time it receives the detection data RD arriving at every 1H, thereby reducing the noise component contained in the detection data RD. After performing the process, the detection data is stored and held. Thus, as shown in FIG. 2B, the high frequency noise component K0 based on the unevenness of each pixel included in the detection data RD (FIG. 2A) is suppressed and converted into a small noise component K1. The input data S1 will be sent from the picture memory 7.

Here, the defect signals WD and BD based on the abnormality of the pixel of the solid-state image sensor 1 and the shading component SH that fluctuates slowly during the 1H period are sent to the input data S1 as they are. Here, since the shading component SH has the property of changing with a similar tendency with respect to the entire line signal for 1H that sequentially arrives, it is output as it is without being suppressed by the synchronous addition for each frame. Further, since the defect signals WD and BD are generated as a similar signal when a plurality of adjacent line signals are generated, they are not suppressed and remain as they are. As a solid-state image sensor 1
This is because when CCD is used, the anomaly that occurs in the pixel is not continuous in the H direction in most cases and is continuous only in the V direction due to its nature.

The input data S1 having such a signal content is input to the defect removing filter 9. The defect removing filter 9 is composed of a 1 × 5 median filter as shown in FIG. 5, and the intermediate value of the data of 5 pixels successively following one line signal of the input data S1 is set to the intermediate position data. As. That is, in FIG. 5, the data "40" of the i-th pixel (whose address is xij) included in the j-th line output of the input data S1 is the central bit position, that is, the third bit position. The data "12" and "10" of the pixels of addresses x (i-1) j and x (i-2) j which are successively connected are stored in the second and first bit positions M2 and M1 while being input to M3. And address x (i + 1) j, x (i + 2)
The data "9" and "11" of j are set to the fourth and fifth bit positions M.
Input to M4. In this state, the filter 9 outputs the data representing the intermediate value of the data input to the first to fifth bit positions M1 to M5 (the fifth bit data "11" in this embodiment). Is output as output S2.

In this operation, the content "40" of the data input to the third bit position M3 shows a large value representing a white defect, while the other first, second, fourth and fifth bit positions M1. , M2, M4, M5 contents "10", "12",
"9" and "11" have signal levels indicating that the corresponding pixels are normal. In such a case, the median filter operation selects the data at the central position xij as the intermediate value data "11" (data at the address x (i + 2) j) and sends it as the output S2. In this way, the defect removing filter 9 can send the filter output S2 from which the defect is removed even if the input data S1 contains a defect.

When the 1 × 5 median filter is used as the defect removing filter 9 as described above, the defect removing operation cannot be performed if there are three or more defects in 5 consecutive bits of line input. In this case, it is determined that the solid-state image sensor under inspection is defective.

This filter output S2 is input to the buffer memory 10,
Noise components are further suppressed by performing simultaneous addition operation using the accumulator 8 and then the shaded extraction output S3 as shown in FIG. 2C is transmitted. Here, the shielding extraction output S3 is the filter output S2 (second
The defect data WD and BD are removed and the noise component K2 based on the unevenness of each pixel is further reduced as compared with FIG. This shielding extraction output S
3 is given to the low pass filter 11.

This low-pass filter 11 outputs the shielding extraction output S3.
For smoothing the noise component K2 contained in, for example, a 3 × 3 low pass filter as shown in FIG. 6 or 7 can be applied. Thus, at the output end of the low-pass filter 11, as shown in FIG. 2 (D), a smoothed output S4 consisting of substantially only the fading component SH is obtained, and this is supplied to the peripheral edge interpolation circuit 12.

The peripheral edge interpolating circuit 12 cannot avoid the occurrence of a blank area which cannot be calculated by calculation in the peripheral edge portion of the solid-state image pickup device 1 during the processing in the defect removal filter 9 and the low-pass filter 11, so that the data in this blank area is inevitable. Is interpolated so that the subsequent processing can be performed. Incidentally, if there is a pixel group for which it is not actually determined whether or not the solid-state image sensor 1 can be used for the outer peripheral edge portion, the peripheral edge portion cannot perform the photoelectric conversion function, so the solid-state image sensor is effectively used. In order to do so, it is better that there is no such undecidable area.

In practice, if the defect removing filter 9 is a 1 × 5 median filter and the low pass filter 11 is a 3 × 3 filter, as in the embodiment of FIG.
As shown in FIG. 8, the smoothed output S4 has three-bit blank areas 21 and 22 at the outer peripheral edge in the H direction, and one-bit blank areas 23 and 24 at the outer peripheral edge in the V direction.
The blank areas 21 to 24 are separated by the peripheral interpolation circuit 12 into the ninth area.
The interpolation calculation is performed in the order shown in the figure.

That is, first, the blank area 21 on the left side edge portion is interpolated using the data D1 of the pixel group of 3 bits inside the blank area 21 as shown in FIG. Thus, as shown in FIG. 9B, two data areas having the same data D1 are contiguously formed on the left peripheral portion.

Next, the peripheral portion interpolation circuit 12 interpolates the data D2 of the pixel group of one bit inside the blank area 23 of the upper edge portion and has the same data D2 as shown in FIG. 9C. Interpolation is performed to connect two data areas. Next, as shown in FIG. 9C, the peripheral portion interpolation circuit 12 sets the blank area 22 on the right side edge to the data D3 inside the blank area 22.
Thus, the interpolation calculation is performed, and as a result, two areas having the same data D3 are formed so as to be connected to each other, as shown in FIG. 9 (D).

Thereafter, the peripheral edge interpolation circuit 12 interpolates the data D4 inside the blank area 24 at the lower edge, and thus the ninth area
As shown in FIG. 6E, two areas having the same data D4 are formed at the lower edge.

In this way, the interpolated output S5 generates the interpolated output S5 having corresponding data over the entire pixels of the solid-state image pickup device 1, and the subtraction circuit 13 subtracts the interpolated output S5 from the input data S1 sent from the picture memory 7.

Here, the input data S1 is the detection data RD obtained in the solid-state imaging device 1 as described above with reference to FIG.
Since the data is the same as that when the noise component K0 in FIG. 2 (A) is suppressed, the output of the pixels of the entire solid-state image pickup device 1 is output including the peripheral part. Therefore, the subtraction output S6 of the subtraction circuit 13 is the input data S1 (see FIG. 1).
From (B)), the shading component SH is interpolated to output S5.
By subtracting the white defect WD and the black defect B
Only D will be output.

Since such subtraction is performed over the front surface including the outer peripheral edge portion of the solid-state image sensor 1, if the white defect WD or the black defect BD occurs in the peripheral pixel, it can be reliably detected. Incidentally, the same data as the data of the pixel group inside is interpolated in the signal component corresponding to the outer peripheral edge portion of the interpolation output S5, but in reality, a curve similar to the curve at the outer edge portion of the shaded curve SH is used. Since it can be obtained, it is possible not to leave the influence of the shaded waveform on the subtraction result with the input data S1.

The subtraction output S6 of the subtraction circuit 13 is input to the defect determination circuit 14.

When the defect judgment circuit 14 receives the subtraction output S6, FIG.
For example, four comparison levels COM1 to COM4 are set as shown in FIG. 3, and the defect WD or BD is determined by these comparison levels COM1 to COM4.
It is determined whether or not Based on the result of the determination, firstly, the number of defects is integrated to perform so-called score calculation, thereby evaluating the score of the solid-state image sensor 1 currently inspected.

Secondly, the defect judgment circuit 14 detects the address where the defect WD or BD occurs and performs so-called shape recognition, score calculation, and post-processing.

Thirdly, the defect determination circuit 14 creates a defect map representing the distribution and size of defects based on the shape recognition and score calculation.

Thus, the defect judgment circuit 14 sends out the defect detection signal ADD containing the result of the defect judgment.

In the above configuration, the solid-state image sensor 1 to FIG.
When the detection data RD as shown in FIG. 3 is obtained, the filter output S2 becomes only the fading component SH as shown in FIG. Filter
After the smoothing in 11, the interpolation calculation is performed in the rear edge interpolation circuit 12. When the subtraction circuit 13 subtracts from the input data S1 using the interpolation output S5, the subtraction output S6 becomes the tenth value.
As shown in FIG. 6C, it is possible to obtain the same signal as that when the defects WD and BD are separated and extracted from the shielding component SH. Therefore, in the defect determination circuit 14, the defect W
The addresses of D and BD can be easily distinguished.

In the case of the embodiment shown in FIG. 5, the defect removing filter 9 has a 1 × 5 median filter structure for black and white images.
The configuration shown in Fig. 11 may be applied. That is, as shown in FIG. 11 (A), the solid-state image sensor 1 has three primary color signals R, G,
It has a configuration in which pixels corresponding to B are sequentially arranged,
Since a unique color filter is attached to each pixel of the three primary color signals, it is necessary to filter the defect removing filter 9 for each color. In such a case, the 11th color signal for each primary color signal R, G, B is obtained.
As shown in FIG. 2B, the mask portion SK for 2 bits is provided in the middle.
The primary color signals may be separated from each other by using the mask 21 having the above-mentioned structure and the separated output may be applied to the median filter.

FIG. 12 shows still another embodiment of the defect removing filter 9, which compares two adjacent data bits of the input data S1 extracted from the picture memory 7 and compares the maximum value or the minimum value thereof. The selection is made to obtain a filter output which does not include a black defect or a white defect.

In this embodiment, the defect removing filter 9 is the pixel xij.
In order to obtain the filter output S2 of each of the two adjacent bits, the data of adjacent five bits are used.
Select the maximum value of the two bit data, select the minimum value of the adjacent data in the second step for the selected output, and select the minimum value of the selected adjacent data in the third step. , In the fourth step, the maximum value of the two data is selected. In this way, the filter output can be obtained by removing the data due to the defect based on the defective pixel as the data at the pixel xij position. 5th to hide
The calculation of the median filter shown in the figure can be used as a simple configuration instead of a device having a problem that it takes too much time or cannot be applied in hardware.

Further, instead of the defect removing filter 9 described above, a structure using a space filter or a two-dimensional filter may be applied.

When processing a color image as the low-pass filter 11 having the configuration shown in FIG. 1, the one having the configuration shown in FIG. 13 can be applied. That is, the shading output S3 received from the buffer memory 10 is stored in the memory area M11 as shown in FIG.
First, the memory M11 is shifted downward by one bit and the data R
2 is taken in, then the memory M11 is shifted upward by 1 bit and the lower data R3 is taken in, and then the memory M11 is shifted right by 1 bit and the data R4 is taken in.

Then, the low-pass filter 11 obtains the averaged output MW using the following equation (1) MW = (R1 + R2 + R3 + R4) / 4 (1) and sends it as the smoothed output S4.

By using the low-pass filter 11 that performs signal processing in this manner, it is possible to realize a low-pass filter that can be applied to image signals of any color pattern and that can simultaneously process all pixels.

〔The invention's effect〕

As described above, according to the present invention, in order to obtain the shaded extraction output in the shaded extraction circuit, when the detection data is arithmetically processed by the defect removal filter,
Although it becomes impossible to obtain the shaded extraction output for the pixels in the peripheral portion of the solid-state imaging device 1, the data of the pixel group in the peripheral portion of this shaded extraction output should be interpolated as the data of the pixel group in the blank area. By doing so, when subtracting the shielding component contained in the extracted data by the shielding extraction output, it is possible to surely remove the shielding component for the pixels at the peripheral portion of the solid-state image sensor, and thus the solid-state imaging can be performed. It is possible to reliably detect a defect generated in the outer peripheral edge portion of the element.

[Brief description of drawings]

FIG. 1 is a block diagram showing an embodiment of a defect detecting device for a solid-state image pickup device according to the present invention, FIG. 2 is a signal waveform diagram showing signals of respective portions thereof, and FIG. 3 is an explanation of a spatial filter used conventionally. FIG. 4 is a schematic diagram showing a blank area produced when a spatial filter is used, and FIG. 5 is a schematic diagram showing the defect removing filter 9 of FIG. 1, 6, and 7.
1 is a table showing the low-pass filter 11 of FIG. 1, FIGS. 8 and 9 are schematic diagrams for explaining the interpolation operation of the peripheral portion interpolation circuit 12 of FIG. 1, and FIG. 10 is the configuration of FIG. Signal waveform diagram of each part showing the experimental result of the defect detection device by
FIG. 12 is a schematic diagram showing another embodiment of the defect removing filter 9 of FIG. 1, and FIG. 13 is a schematic diagram showing another embodiment of the low-pass filter 11 of FIG. DESCRIPTION OF SYMBOLS 1 ... Solid-state image sensor, 2 ... Light source, 3 ... Clock driver, 6 ... Shading extraction circuit, 7 ... Picture memory, 8 ... Akymulator, 9 ... Defect removal filter, 10 ... Buffer memory, 11 ...... Low-pass filter, 12 ...... peripheral part interpolation circuit, 13 …… subtraction circuit, 14 …… defect judgment circuit.

Claims (2)

[Claims] 1. A shading extraction circuit for receiving detection data obtained from a solid-state image sensor to extract first shading data by digital calculation, and the above-mentioned one of the extracted first shading data. The data of the second pixel group arranged inside the first pixel group in the area of the outer peripheral edge of the solid-state imaging device is interpolated as second shading data corresponding to the first pixel group. And a subtraction circuit that subtracts the output data of the peripheral interpolation circuit from the detection data and outputs a defect detection signal that is a defect signal included in the detection data. Defect detection device for solid-state image sensor. 2. A shading extraction circuit includes a filtering circuit for removing a defective signal from output data of a picture memory for storing data in which noise components are reduced by synchronously adding the detected data. The defect detection device for a solid-state image pickup device according to claim 1.