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Algorithms for Masking Pixel Defects at Low Exposure Conditions for CMOS Image Sensors

Abstract Full-Text HTML Download Download as PDF (Size:5240KB) PP. 220-227
DOI: 10.4236/eng.2010.24032    5,726 Downloads   9,726 Views   Citations
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Vinesh Sukumar, Jason Tanner, Atif Sarwari, Herbert L Hess




This paper introduces certain innovative algorithms to mask for pixel defects seen in image sensors. Pixel defectivity rates scale with pixel architecture and process nodes. Smaller pixel and process nodes introduce more defects in manufacturing. Brief introduction to causes for pixel defectivity at lower pixel nodes is explained. Later in the paper, popular defect correction schemes used in image processing applications are discussed. A new approach for defect correction is presented and evaluated using images captured from an 8M Bayer image sensor. Experimentation for threshold evaluation is done and presented with practical results for better optimization of proposed algorithms. Experimental data shows that proposed defect corrections preserves a lot of edge details and corrects for bright and hot pixels/clusters, which are evaluated using histogram analysis.


Hot Pixels, Pixel Clusters, Defect Correction, Cluster Correction

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V. Sukumar, J. Tanner, A. Sarwari and H. Hess, "Algorithms for Masking Pixel Defects at Low Exposure Conditions for CMOS Image Sensors," Engineering, Vol. 2 No. 4, 2010, pp. 220-227. doi: 10.4236/eng.2010.24032.

Conflicts of Interest

The authors declare no conflicts of interest.


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