Abstract
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.
Highlights
Digital imaging systems capture the spectrum or color information of physical stimuli by filtering the object image through color filters with different spectral transmittances, and transform the photon signal into electronic signal which is quantized into digital counts with electronic sensors [1]
This paper introduces certain innovative algorithms to mask for pixel defects seen in image sensors
All test images used are taken from an 8M CMOS image sensor
Summary
Digital imaging systems (including digital still camera, digital video camera etc) capture the spectrum or color information of physical stimuli by filtering the object image through color filters with different spectral transmittances, and transform the photon signal into electronic signal which is quantized into digital counts with electronic sensors [1]. Electronic sensors generally are based on Charge-Coupled Device (CCD) or Active Pixel Sensor (APS) Complimentary MOS technology. This digital information produced by these electronic sensors, ignoring all non-idealities of CMOS/CCD imager optics and pixels, must undergo some image processing functions prior to display on any visual media or data storage in Red Green Blue (RGB) format. These solid-state image sensors develop in-field defects in all common APS CMOS manufacturing environments. This is more challenging for smaller pixel geometries. Performance metrics and tradeoffs are presented in the latter half of the paper
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