Noise reduction in CMOS image sensors
     for high quality imaging: The
 autocorrelation function filter on burst
       ...
Noise in image sensor
                          RST
                     Tx
                                              ...
Principle of an ACF
    The data is collected at the same interval time.
    Autocorrelation value is calculated accordi...
1D simulation of ACF
                 (A) cosine wave
                                        Block diagram of 1-D ACF met...
Expansion ACF method to 2-D model
Time




                               V
                    Image




                ...
ACF value as a function of pixel intensity
                                                         (A)
       Auto Correl...
The algorithm of noise judging and filtering process
          by a time domain ACF method
                 Image data (BM...
Result of image processing
・     Reduction of random noise is possible per pixel.
・     Since filter processing is not per...
The algorithm and the example of processing of a
            time domain ACF method

                    Image data (BMP,R...
Image processing result as a function of threshold
     value both pixel value and ACF value




                         ...
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D1150740001

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Noise Reduction in CMOS Image Sensors for High Quality Imaging The Autocorrelation Function Filter on Burst Image Sequences


Kazuhiro Hoshino (1), Frank Nielsen (2,3), Toshihiro Nishimura (4)
(1) Image Sensor Business Group, Sony Corporation, 4-14-1 Asahi-chou, Atsugi-shi, Kanagawa, Japan
(2) Sony Computer Science Laboratories, Inc. 3-14-13 Higashi Gotanda, Shinagawa-ku, Tokyo, Japan
(3) École Polytechnique, LIX, F-91128 Palaiseau Cedex, France
(4) Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu, Kitakyushu, Fukuoka, Japan

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D1150740001

  1. 1. Noise reduction in CMOS image sensors for high quality imaging: The autocorrelation function filter on burst image sequences Kazuhiro Hoshino1, Frank Nielsen2,3, Toshihiro Nishimura4 1 Image Sensor Business Group, Sony Corporation, 4-14-1 Asahi-chou, Atsugi-shi, Kanagawa, Japan Kazuhiro.Hoshino@jp.sony.com, 2 Sony Computer Science Laboratories, Inc. 3-14-13 Higashi Gotanda, Shinagawa-ku, Tokyo, Japan Frank.Nielsen@acm.org 3 Ecole Polytechnique, LIX F-91128 Palaiseau Cedex, France 4 Graduate School of Information, Production and Systems, Waseda University 2-7 Hibikino, Wakamatsu, Kitakyushu, Fukuoka, Japan toshi-hiro@waseda.jp
  2. 2. Noise in image sensor RST Tx Image pixel P Offset noise(C) N+ Reset noise(W) N SEL Col. Bus 1/f noise(W ) Dark noise(C) Dark shot noise( W ) n Photon shot noise( W ) Condensing Gm(C) V Decoder Amp noise( W) Analog circuit (Condenser, CDS, Decoder) Amp noise( W ) Offset noise(C) Condensing Gm(C) 1/f noise( W) TG Programmable Gain Amp CMOS image sensor W white noise, C colored noise.
  3. 3. Principle of an ACF  The data is collected at the same interval time.  Autocorrelation value is calculated according to the following equation. N 1 1 R( ) x(t ) x(t ) N t 0 R is ACF value. N is the number of data, t is time. x is pixel value, and τ is shifted time.
  4. 4. 1D simulation of ACF (A) cosine wave Block diagram of 1-D ACF method (B) white noise wave Sampling Make Calculation + In same base wave ACF value interval time Make noise wave white noise wave Original wave ACF value (A) cosine wave (B) white noise wave
  5. 5. Expansion ACF method to 2-D model Time V Image H H direction N 1 1 R( ) x(t ) x(t ) N t 0 R is ACF value. N is the number of data which were sampled in time axis, t is time. x is pixel value, and τ is shifted time.
  6. 6. ACF value as a function of pixel intensity (A) Auto Correlation Value Pixel-A (B) Pixel-B Flame Number Bright pixel A (180 in 256 scale) and dark pixel B (8 in 256 scale)
  7. 7. The algorithm of noise judging and filtering process by a time domain ACF method Image data (BMP,RAW) Pixel value extraction Pixel value i<10 No Calculation of ACF ACF value r<0.8 No Leveling filter processing Pixel value decision I< Total pixel number No END
  8. 8. Result of image processing ・ Reduction of random noise is possible per pixel. ・ Since filter processing is not performed in a bright pixel, resolution does not deteriorate. Original image Processing image
  9. 9. The algorithm and the example of processing of a time domain ACF method Image data (BMP,RAW) Pixel value extraction Pixel value i<10 No Calculation of ACF ACF value r<0.8 No Leveling filter processing Pixel value decision I< Total pixel number No END
  10. 10. Image processing result as a function of threshold value both pixel value and ACF value Original Ith= 100 Rth=0.985 Ith= 100 Ith= 100 Rth=0.995 Rth=1.000
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