Open Access Journal

ISSN : 2394 - 6849 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

ISSN : 2394-6849 (Online)

Noise Reduction in CMOS Image Sensor for High Quality Imaging Using ACF

Author : Manjunath.T.N 1 Praveen Kumar 2 Ashish Parate 3 Narendra Kumar 4

Date of Publication :7th May 2016

Abstract: The new method for image noise detection and reduction in complementary metal oxide semiconductor (CMOS) image sensors inspired from audio noise cancelling techniques. Our algorithm is based on computing efficiently the time-dependent pixel autocorrelation function (ACF) from constant time interval acquired sequences of images. This demonstrate the effectiveness of approach for successfully detecting and reducing white noise. Further, consider an adaptive filter that exhibits significant computational improvements making it highly practical. Finally, the report on experiments displaying the high-quality imaging systems obtained in practice.

Reference :

  1. [1] Nie, K.; Yao, S.; Xu, J.; Gao, J. Thirty Two-Stage CMOS TDI Image Sensor With On-Chip Analog Accumulator. IEEE Trans. Very Larg. Scale Integr. (VLSI) Syst. 2014, 22, 951956.

    [2] Kazuhiro Hoshino, Frank Nielsen, Toshihiro Nishimura Noise Reduction in CMOS Image Sensors for High Quality Imaging: The Autocorrelation Function Filter on Burst Image Sequences ICGST-GVIP Journal, Volume 7, Issue 3, November 2007.

    [3] Richard Alan Peters II A New Algorithm for Image Noise Reduction using Mathematical Morphology IEEE Transactions on Image Processing Volume 4, Number 3, pp. 554-568, May 1995.

    [4] Eero P. Simoncelli, Edward H. Adelson Noise Removal Via Bayesian Wavelet Coring Proceedings of 3rd IEEE International Conference on Image Processing. Vol. I, pp. 379-382. Lausanne, Switzerland. 16-19 September 1996.

    [5] Leonid I. Rudin, Stanley Osher and Emad Fatemi Nonlinear total varia-tion based noise removal algorithms 1992 - Elsevier Science Publishers B.V

    [6] S. Grace Chang, Bin Yu and Martin Vetterli Adaptive Wavelet Thresh-olding for Image Denoising and Compression IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 9, NO. 9, SEPTEMBER 2000.

    [7] Ce Liu, Richard Szeliski, Sing Bing Kang, C. Lawrence Zitnick and William T. Freeman Automatic Estimation and Removal of Noise from a Single Image IEEE Transactions on Pattern Analysis and Machine Intelligence October, 2006.

    [8] Antoni Buades and Jean-Michel Morel A non-local algorithm for image denoising Technical Report 2004-15, CMLA, 2004.

    [9] Peng-lang Shui and Yong-Bo Zhao Image Denoising Algorithm using Doubly Local Wiener Filtering with Block-adaptive Windows in Wavelet Domain Foundation of ANEDD (Project No: 200139), the TRAPOYT, and the NSF (No: 60472086) of P. R. China.

    [10] Box, G. E. P., G. M. Jenkins, and G. C. Reinsel. Time Series Analysis: Forecasting and Control. 3rd ed. Englewood Cliffs, NJ: Prentice Hall, 1994.

    [11] Priyanka Kamboj and Versha Rani A brief study of various noise model and filtering techniques Volume 4, No. 4, April 2013 Journal of Global Research in Computer Science.

    [12] R. Boyle and R. Thomas Computer Vision: A First Course, Blackwell Scientific Publications, 1988, pp 32 34

    [13] Prof. William H. Press Computational Statistics with Application to Bioinformatics- Wiener Filtering Spring Term, 2008 The University of Texas at Austin.

    [14] Andrew knight Basics of MATLAB and beyond text book 2000 by CRC Press LLC.

    [15]http://file:///F:/pr1/image- Wikipedia, the freeencyclopedia.htm


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