CN102006430B - Noise removing method applied to image sensor and relevant device - Google Patents
Noise removing method applied to image sensor and relevant device Download PDFInfo
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- CN102006430B CN102006430B CN 200910168648 CN200910168648A CN102006430B CN 102006430 B CN102006430 B CN 102006430B CN 200910168648 CN200910168648 CN 200910168648 CN 200910168648 A CN200910168648 A CN 200910168648A CN 102006430 B CN102006430 B CN 102006430B
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Abstract
The invention discloses a noise removing method which comprises the steps of: comparing a pixel value of a target pixel with pixel values of a plurality of vicinal pixels, wherein the target pixel and the vicinal pixels correspond special color components; aiming at each vicinal pixel in the plurality of vicinal pixels, checking whether the difference of the pixel value of the vicinal pixel and the pixel value of the target pixel is less than the special noise critical value or not, and setting the pixel value of the vicinal pixel to be a similar vicinal pixel when the difference of the pixel value of the vicinal pixel and the pixel value of the target pixel is less than the special noise critical value; and updating the pixel value of the target pixel according to the pixel value of the target pixel and the pixel value of each similar vicinal pixel.
Description
Technical field
The present invention relates to image processing, refer to that especially a kind of specific noise critical value of utilizing is to remove method and the relevant apparatus of noise in the image sensor.
Background technology
In image system, three kinds of hue components must side by side be captured in order to can accurately express the content of image, and can capture the digital image acquiring system of three kinds of hue components simultaneously for construction, often need to use three independently image sensors, thus, to cause production cost too high and make product structure become very complicated, so, for reaching, the cost that makes the digital image acquiring system and size minimize, image sensor arrays in the digital image acquiring system (being made of a plurality of silicon) also must allow its size reduce, in other words, the number of color sampling just must be a less numerical value.A kind of feasible method is that the data that make each image sensor in the image acquisition system only collect single color produce the pick-up image with low data bulk, so, generally speaking image acquisition system just adopts mosaic color filter (Mosaic Color Filter), wherein this mosaic color filter can be known as color filter lens array (Color Filter Array again, CFA), therefore, image acquisition system just obtains pick-up image via one of three kinds of hue components of sampling resulting color array, and wherein this color array stores the single color composition that it comprises at each pixel.Because other two kinds of hue components of each pixel are ignored by the image sensing system, therefore, for each pixel, the original sense data that the image sensing system obtains just comprises less color sampling.Because the corresponding pixel of each filter in the color filter lens array and the hue component that only allows to be positioned at special frequency band pass through, therefore before institute's picked image was further processed or shows, the hue component that each pixel lacks just must be rebuild earlier so that each pixel energy comprises three kinds of all hue components.
But, no matter how perfect the video camera specification is, is perfectly absolute without any image still, and image can be disturbed because of the existence of noise.In digitized video, the main source of noise is to occur between image capture, digitlization and/or transmission period.The performance of image sensor is subjected to the influence of several factors, it similarly is ambient conditions during image capture, and the quality of sensing element itself, for example, at charge coupled cell (Charge-Coupled Device, CCD) in the image capture of camera, the temperature of luminosity and transducer is the key factor of the influence noisiness in the image that produces.
Filter digitized video with attenuate acoustic noise in the process of protection image detail; it is necessary processing step in the image processing; for example, because many application all are based on the operator that the application of image computing draws, so any noise all can cause the grave error result in the image.So, the purpose of noise attentuation not only will be improved visual quality, and more can promote the usefulness of subsequent treatment work, for example coding (coding), analyze cutting (analysis cutting), identification (identification) or explain (interpretation) etc.
Summary of the invention
Therefore, one of purpose of the present invention is to provide a kind of specific noise critical value of utilizing to remove method and the relevant apparatus of noise in the image sensor, to avoid removing unnecessary noise as much as possible under the situation that causes image edge and details to blur.
According to one embodiment of the invention, it discloses a kind of noise remove method that is applied to image sensor, described image sensor comprises specific color filter lens array and pel array, described pel array includes a plurality of pixels, one of them of all corresponding a plurality of colour components of each pixel, described noise remove method includes:
The pixel value of comparison object pixel and the pixel value of a plurality of neighborhood pixels, wherein said object pixel and all corresponding specific color composition of described a plurality of neighborhood pixels;
At each neighborhood pixels in described a plurality of neighborhood pixels:
Utilize check circuit to check whether the pixel value of described neighborhood pixels is similar to the pixel value of described object pixel; And
When the pixel value of described neighborhood pixels and the pixel value of described object pixel are identified as when similar, described neighborhood pixels is made as similar neighborhood pixels; And
Upgrade the pixel value of described object pixel according to the pixel value of the pixel value of described object pixel and each similar neighborhood pixels,
Wherein when the difference of the pixel value of the pixel value of described neighborhood pixels and described object pixel during less than the specific noise critical value, it is similar that the pixel value of described neighborhood pixels and the pixel value of described object pixel are identified as,
Described method also includes:
Set described specific noise critical value according to the position of described object pixel in described image sensor;
Wherein when described object pixel was arranged in described image sensor primary importance, described specific noise critical value was set as first value; And when described object pixel was arranged in the described image sensor second place, described specific noise critical value was set as second value that is different from described first value, and the wherein said second place is different from described primary importance,
The more described second place of wherein said primary importance is near the center of described image sensor, and described first value is less than described second value.
According to another embodiment of the present invention, it discloses a kind of noise remove device that is applied to image sensor, described image sensor comprises specific color filter lens array and pel array, described pel array includes a plurality of pixels, one of them of all corresponding a plurality of colour components of each pixel, described noise remove device includes:
Comparison circuit, in order to the pixel value of comparison object pixel and the pixel value of a plurality of neighborhood pixels, wherein said object pixel and all corresponding specific color composition of described a plurality of neighborhood pixels;
Check circuit is coupled to described comparison circuit, wherein at each neighborhood pixels in described a plurality of neighborhood pixels:
Described check circuit checks whether the pixel value of described neighborhood pixels is similar to the pixel value of described object pixel, and be identified as when similar when the pixel value of described neighborhood pixels and the pixel value of described object pixel, described check circuit is made as similar neighborhood pixels with described neighborhood pixels, wherein when the difference of the pixel value of the pixel value of described neighborhood pixels and described object pixel during less than the specific noise critical value, the pixel value of described neighborhood pixels is identified as similar to the pixel value of described object pixel;
The pixel value refresh circuit is coupled to described check circuit, upgrades the pixel value of described object pixel in order to the pixel value according to the pixel value of described object pixel and each similar neighborhood pixels; And
The critical value setting circuit, be coupled to described check circuit, and in order to set described specific noise critical value according to the position of described object pixel in described image sensor, wherein when described object pixel is arranged in described image sensor primary importance, described specific noise critical value is set as first value, and when described object pixel is arranged in the described image sensor second place, described specific noise critical value is set as second value that is different from described first value, the wherein said second place is different from described primary importance, the more described second place of wherein said primary importance is near the center of described image sensor, and described first value is less than described second value.
Embodiments of the invention provide a kind of specific noise critical value of utilizing to remove method and the relevant apparatus of noise in the image sensor, also can protect image edge and all the other image details simultaneously.
Description of drawings
Fig. 1 is applied to the schematic diagram of an embodiment of the noise remove device of image sensor for the present invention;
Fig. 2 A is the schematic diagram of an embodiment of image sensor of the present invention;
Fig. 2 B is the schematic diagram of another embodiment of image sensor of the present invention;
Fig. 2 C is the schematic diagram of another embodiment again of image sensor of the present invention;
Fig. 3 is applied to the flow chart of an embodiment of the noise remove method of image sensor for the present invention.
Embodiment
In the middle of specification and follow-up claim, used some vocabulary to censure specific element.Those skilled in the art should understand, and hardware manufacturer may be called same element with different nouns.This specification and follow-up claim are not used as distinguishing the mode of element with the difference of title, but the criterion that is used as distinguishing with the difference of element on function.Be open term mentioned " comprising " in the middle of specification and the follow-up claim in the whole text, so should be construed to " comprise but be not limited to ".In addition, " couple " word and refer to comprise any indirect means that are electrically connected that directly reach at this.Therefore, be coupled to second device if describe first device in the literary composition, then represent this first device and can directly be electrically connected in this second device, or be electrically connected to this second device indirectly by other device or connection means.
With reference to figure 1, Fig. 1 is applied to the schematic diagram of an embodiment of the noise remove device 100 of image sensor for the present invention.Noise remove device 100 utilizes specific noise critical value Vs to remove the noise of image sensor, and this image sensor comprises specific color filter lens array and pel array, each pixel all corresponds to a color filter, thereby corresponds to a plurality of colour components one of them.For convenience of explanation, embodiments of the invention are represented this specific color filter lens array with Baeyer (Bayer) color filter lens array, yet this only is the usefulness as the example explanation, is not to be restriction of the present invention.
For each the neighborhood pixels Pn in these selected a plurality of neighborhood pixels, whether the difference Diff between the pixel value of check circuit 20 meeting inspection neighborhood pixels Pn and the pixel value of object pixel Pt is less than specific noise critical value Vs, in this embodiment, as the difference Diff of the pixel value of the pixel value of neighborhood pixels Pn and object pixel Pt during less than specific noise critical value Vs, check circuit 20 just is set at similar neighborhood pixels with neighborhood pixels Pn.
Pixel value refresh circuit 30 is coupled to check circuit 20, upgrades the pixel value of object pixel Pt in order to the pixel value of each similar neighborhood pixels of assert according to the pixel value of object pixel Pt and by check circuit 20.Critical value setting circuit 40 is coupled to check circuit 20, and in order to setting specific noise critical value Vs according to object pixel Pt, and the pixel value of how setting specific noise critical value Vs and upgrading object pixel Pt will be illustrated in follow-up embodiment.
In the lump with reference to figure 1 and Fig. 2 A.Fig. 2 A is the schematic diagram of an embodiment of image sensor 200 of the present invention.As shown in Fig. 2 A, image sensor 200 comprises the pixel G of corresponding green tint composition
1-G
13, the pixel R of corresponding red color composition
1-R
6, and the pixel B of corresponding blue colour component
1-B
6Because noise is common than being seen easily in green pixel, so critical value setting circuit 40 just can be set specific noise critical value Vs according to the colour component of object pixel Pt in redness and blue pixel.When object pixel Pt is that green pixel in the image sensor 200 is (as pixel G
1) time, critical value setting circuit 40 is made as the first color-values C1 with specific noise critical value Vs; When object pixel Pt is that red pixel in the image sensor 200 is (as pixel R
1) time, critical value setting circuit 40 is made as specific noise critical value Vs the second color-values C2 that is different from the first color-values C1; When object pixel Pt is that image sensor 200 Smalt pixels are (as pixel B
1) time, critical value setting circuit 40 is made as specific noise critical value Vs the 3rd color-values C3 that is different from the first color-values C1.
Pixel G with corresponding green tint composition
7Be example as object pixel Pt, comparison circuit 10 is object pixel G in the image sensors 200 relatively
7Pixel value and a plurality of neighborhood pixels G
1, G
2, G
3, G
4, G
5, G
6, G
8, G
9, G
10, G
11, G
12, G
13Pixel value.Please note that selected pixel is only as the usefulness of example explanation in above-described embodiment, in other words, the mode of choosing of the neighborhood pixels around the object pixel can be done the elasticity adjustment according to different design requirements.
Check circuit 20 checks neighborhood pixels G
1Pixel value and object pixel G
7Pixel value between the first difference Diff_1 whether less than the first color-values C1, if check circuit 20 judges that the first difference Diff_1 is less than the first color-values C1, then with neighborhood pixels G
1Be made as similar neighborhood pixels.Next, check circuit 20 continues to check another neighborhood pixels G
2Pixel value and object pixel G
7Pixel value between the second difference Diff_2 whether also less than the first color-values C1, if check circuit 20 judges that the second difference Diff_2 is less than the first color-values C1, then with neighborhood pixels G
2Be made as similar neighborhood pixels, the rest may be inferred.After check circuit 20 is finished above-mentioned inspection operation, if neighborhood pixels G
3, G
5, G
8, G
10Be identified as similar neighborhood pixels, then 30 couples of object pixel G of pixel value refresh circuit
7Pixel value and similar neighborhood pixels G
3, G
5, G
8, G
10Pixel value average to upgrade object pixel G
7Pixel value, more specifically, object pixel G
7The renewal pixel value can be shown in following formula (1):
In formula (1), Pixel_G
7, Pixel_G
3, Pixel_G
5, Pixel_G
8, Pixel_G
10Represent object pixel G respectively
7And similar neighborhood pixels G
3, G
5, G
8, G
10Pixel value.
With reference to figure 2B, Fig. 2 B is the schematic diagram of another embodiment of image sensor 200 of the present invention.In this embodiment, as 30 couples of object pixel G of pixel value refresh circuit
7Pixel value and similar neighborhood pixels G
3, G
5, G
8, G
10Pixel value when averaging, pixel value refresh circuit 30 can be according to object pixel G
7To similar neighborhood pixels G
3, G
5, G
8, G
10Between distance set the weighted value of each similar neighborhood pixels, that is to say object pixel G
7The renewal pixel value can be tried to achieve by the weighted average computing.For instance, as shown in Fig. 2 B, object pixel G
7To similar neighborhood pixels G
5, G
10Distance be D1, so similar neighborhood pixels G
5, G
10Weighted value can be made as the first weighted value W1 according to this; Similarly, object pixel G
7To similar neighborhood pixels G
8Distance be D2, so similar neighborhood pixels G
8Weighted value can be made as the second weighted value W2 according to this, and object pixel G
7To similar neighborhood pixels G
3Distance be D3, therefore similar neighborhood pixels G
3Weighted value can be made as the 3rd weighted value W3 according to this.Object pixel G
7The renewal pixel value can be shown in following formula (2):
In formula (2), Pixel_G
7, Pixel_G
3, Pixel_G
5, Pixel_G
8, Pixel_G
10Represent object pixel G respectively
7And similar neighborhood pixels G
3, G
5, G
8, G
10Pixel value.Yet this embodiment only is the usefulness as example explanation of the present invention, is not to be restriction of the present invention, and those skilled in the art can adopt other averaging method to draw the renewal pixel value of object pixel.
With reference to figure 2C, Fig. 2 C is the schematic diagram of another embodiment of image sensor 200 of the present invention.Among Fig. 2 C, dashed circle is the one-tenth image circle (Image Circle) of corresponding optical lens, because covering correcting gain (Lens Shading Correction Gain), camera lens can increase corner noise (Corner Noise), so can cause the inhomogeneous of noise profile in the whole one-tenth image circle.For instance, specific noise critical value Vs can be expressed as the product that center noise critical value and camera lens cover correcting gain.Under most situation, noise image edge than image center next obviously.Therefore, critical value setting circuit 40 is set specific noise critical value Vs according to the position of object pixel Pt in image sensor 200.Be example with image sensor 200, as pixel G
7During for object pixel Pt, critical value setting circuit 40 is set at primary importance value L1 with specific noise critical value Vs; Work as pixel B
2, B
5, R
3, R
4During for object pixel Pt, critical value setting circuit 40 is set at the second place value L2 that is different from primary importance value L1 (L2〉L1) with specific noise critical value Vs; As pixel G
4, G
5, G
9, G
10During for object pixel Pt, critical value setting circuit 40 is set at the 3rd positional value L3 that is different from second place value L2 (L3〉L2) with specific noise critical value Vs, by that analogy.In simple terms, when object pixel Pt was arranged in image sensor 200 primary importances, specific noise critical value Vs was set as first value; And when object pixel Pt is arranged in image sensor 200 second places, wherein this primary importance is than the center of this second place near image sensor 200, specific noise critical value Vs is set as second value that is different from this first value, and this first value is less than this second value.After having set specific noise critical value Vs with the diverse location value, other operating procedure of noise remove device 100 is all similar with previous embodiment, so describe in detail just in this omission.
Note that when light intensity reduces the gain of the outside of image sensor 200 will increase and cause simultaneously the enhancing of noise.Therefore, according to another embodiment of the present invention, critical value setting circuit 40 can be set specific noise critical value Vs according to the external gain value of corresponding light intensity.Be example with image sensor 200, when corresponding first brightness value of light intensity, specific noise critical value Vs is set as first shading value (Light Value) V1; And when this light intensity correspondence was different from second brightness value of this first brightness value, specific noise critical value Vs was set as the second shading value V2 that is different from the first shading value V1.In one embodiment, this first brightness value is greater than this second brightness value, and then the first shading value V1 is set as less than the second shading value V2.After having set specific noise critical value Vs with different brightness values, other operating procedure of noise remove device 100 is all similar with previous embodiment, so describe in detail just in this omission.
Note that any design variation in conjunction with technical characterictic in above-described embodiment all belongs to category of the present invention.For instance, specific noise critical value Vs can set according to the colour component of object pixel earlier, gains to adjust setting according to the outside of corresponding light intensity again.In addition, all be applied to the object pixel of corresponding green tint composition (as pixel G though remove the operation of noise in above-described embodiment
7); Yet these operations of removing noise also can be applicable to corresponding other hue component object pixel of (as red or blue).
With reference to figure 3, Fig. 3 is applied to the flow chart of an embodiment of the noise remove method of image sensor for the present invention.In simple terms, this noise remove method is applied to the noise remove device 100 shown in Fig. 1, and in addition, if can obtain identical result haply, step not necessarily will be abideed by order shown in Figure 3 and carry out in regular turn.The step of this noise remove method can briefly be summarized as follows:
Step 301: the pixel value of comparison object pixel and the pixel value of a plurality of neighborhood pixels, wherein this object pixel and all corresponding specific color composition of these a plurality of neighborhood pixels.
Step 303: utilize check circuit 20 to check that whether the difference of pixel value of the pixel value of each neighborhood pixels and this object pixel is less than the specific noise critical value.
Step 305: when the difference of the pixel value of the pixel value of neighborhood pixels and this object pixel during less than this specific noise critical value, this neighborhood pixels is made as similar neighborhood pixels.
Step 307: the pixel value that upgrades this object pixel according to the pixel value of the pixel value of this object pixel and each similar neighborhood pixels.
Note that those skilled in the art after reading the above embodiment of the present invention, should understand the running of step 301-307 in this noise remove method easily, so do not give unnecessary details in addition in this.
In sum, noise remove device 100 of the present invention is effectively removed the noise of pixel in the image sensor by setting suitable noise critical value.The present invention is that design is applied to image sensor, and thus, noise can just be removed at the front end of image processing system, and the noise jamming when avoiding follow-up image processing computing.The specific noise critical value that the present invention mentions can adjust according to the order of severity and the distribution of noise, thereby can make the usefulness of noise remove method and device reach optimization.
The above only is the preferred embodiments of the present invention, and all equalizations of doing according to claim of the present invention change and modify, and all should belong to covering scope of the present invention.
Claims (6)
1. noise remove method that is applied to image sensor, described image sensor comprises specific color filter lens array and pel array, described pel array includes a plurality of pixels, one of them of all corresponding a plurality of colour components of each pixel, and described noise remove method includes:
The pixel value of comparison object pixel and the pixel value of a plurality of neighborhood pixels, wherein said object pixel and all corresponding specific color composition of described a plurality of neighborhood pixels;
At each neighborhood pixels in described a plurality of neighborhood pixels:
Utilize check circuit to check whether the pixel value of described neighborhood pixels is similar to the pixel value of described object pixel; And
When the pixel value of described neighborhood pixels and the pixel value of described object pixel are identified as when similar, described neighborhood pixels is made as similar neighborhood pixels; And
Upgrade the pixel value of described object pixel according to the pixel value of the pixel value of described object pixel and each similar neighborhood pixels,
Wherein when the difference of the pixel value of the pixel value of described neighborhood pixels and described object pixel during less than the specific noise critical value, it is similar that the pixel value of described neighborhood pixels and the pixel value of described object pixel are identified as,
Described method also includes:
Set described specific noise critical value according to the position of described object pixel in described image sensor;
Wherein when described object pixel was arranged in described image sensor primary importance, described specific noise critical value was set as first value; And when described object pixel was arranged in the described image sensor second place, described specific noise critical value was set as second value that is different from described first value, and the wherein said second place is different from described primary importance,
The more described second place of wherein said primary importance is near the center of described image sensor, and described first value is less than described second value.
2. noise remove method as claimed in claim 1, the step of wherein upgrading the pixel value of described object pixel includes:
Carry out the weighted average computing to produce mean value at the pixel value of described object pixel and the pixel value of each similar neighborhood pixels; And
Upgrade the pixel value of described object pixel according to described mean value.
3. noise remove method as claimed in claim 2, the step of wherein upgrading the pixel value of described object pixel also includes:
Set the weighted value of each similar neighborhood pixels according to described object pixel and the distance between the described similar neighborhood pixels;
Wherein when described object pixel was first distance value to the distance of described similar neighborhood pixels, described weighted value was set as first value; When described object pixel and the distance of described similar neighborhood pixels are that described weighted value is set as second value that is different from described first value when being different from the second distance value of described first distance value; And when described first distance value during less than described second distance value, described first value is greater than described second value.
4. noise remove device that is applied to image sensor, described image sensor comprises specific color filter lens array and pel array, described pel array includes a plurality of pixels, one of them of all corresponding a plurality of colour components of each pixel, and described noise remove device includes:
Comparison circuit, in order to the pixel value of comparison object pixel and the pixel value of a plurality of neighborhood pixels, wherein said object pixel and all corresponding specific color composition of described a plurality of neighborhood pixels;
Check circuit is coupled to described comparison circuit, wherein at each neighborhood pixels in described a plurality of neighborhood pixels:
Described check circuit checks whether the pixel value of described neighborhood pixels is similar to the pixel value of described object pixel, and be identified as when similar when the pixel value of described neighborhood pixels and the pixel value of described object pixel, described check circuit is made as similar neighborhood pixels with described neighborhood pixels, wherein when the difference of the pixel value of the pixel value of described neighborhood pixels and described object pixel during less than the specific noise critical value, the pixel value of described neighborhood pixels is identified as similar to the pixel value of described object pixel;
The pixel value refresh circuit is coupled to described check circuit, upgrades the pixel value of described object pixel in order to the pixel value according to the pixel value of described object pixel and each similar neighborhood pixels; And
The critical value setting circuit, be coupled to described check circuit, and in order to set described specific noise critical value according to the position of described object pixel in described image sensor, wherein when described object pixel is arranged in described image sensor primary importance, described specific noise critical value is set as first value, and when described object pixel is arranged in the described image sensor second place, described specific noise critical value is set as second value that is different from described first value, the wherein said second place is different from described primary importance, the more described second place of wherein said primary importance is near the center of described image sensor, and described first value is less than described second value.
5. noise remove device as claimed in claim 4, wherein said pixel value refresh circuit is carried out the weighted average computing with generation mean value at the pixel value of described object pixel and the pixel value of each similar neighborhood pixels, and the pixel value that upgrades described object pixel by described mean value.
6. noise remove device as claimed in claim 5, wherein said pixel value refresh circuit is also set the weighted value of each similar neighborhood pixels according to described object pixel and the distance between the described similar neighborhood pixels; When described object pixel was first distance value to the distance of described similar neighborhood pixels, described pixel value refresh circuit was made as first value with described weighted value; When described object pixel and the distance of described similar neighborhood pixels are when being different from the second distance value of described first distance value, described pixel value refresh circuit is made as described weighted value second value that is different from described first value; And when described first distance value during less than described second distance value, described first value is greater than described second value.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP2006060744A (en) * | 2004-08-24 | 2006-03-02 | Matsushita Electric Ind Co Ltd | Noise reduction apparatus |
| CN1937713A (en) * | 2005-09-19 | 2007-03-28 | 英特尔公司 | Content adaptive noise reduction filtering for image signals |
| US7308153B1 (en) * | 2001-10-11 | 2007-12-11 | Pixelworks, Inc. | Weighted absolute difference based noise reduction method and apparatus |
| CN101212561A (en) * | 2006-12-31 | 2008-07-02 | 华晶科技股份有限公司 | Image noise removing method |
| CN101326808A (en) * | 2005-12-07 | 2008-12-17 | 美光科技公司 | Method and apparatus providing noise reduction while preserving edges for imagers |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7308153B1 (en) * | 2001-10-11 | 2007-12-11 | Pixelworks, Inc. | Weighted absolute difference based noise reduction method and apparatus |
| JP2006060744A (en) * | 2004-08-24 | 2006-03-02 | Matsushita Electric Ind Co Ltd | Noise reduction apparatus |
| CN1937713A (en) * | 2005-09-19 | 2007-03-28 | 英特尔公司 | Content adaptive noise reduction filtering for image signals |
| CN101326808A (en) * | 2005-12-07 | 2008-12-17 | 美光科技公司 | Method and apparatus providing noise reduction while preserving edges for imagers |
| CN101212561A (en) * | 2006-12-31 | 2008-07-02 | 华晶科技股份有限公司 | Image noise removing method |
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