Human eye can generally distinguish objects from each other or from their background, if the difference in luminance or color is large. This paper concentrates on the luminance portion and makes an attempt to characte...Human eye can generally distinguish objects from each other or from their background, if the difference in luminance or color is large. This paper concentrates on the luminance portion and makes an attempt to characterize perception detection to varying contrast which is explained in contrast sensitivity terms. This is accomplished using sinusoidal test patterns. Influence of illumination on perception threshold is also shown in this paper. Practical measurements are done using a calibrated monitor with image capture accomplished with a 1/4' 1.3M camera module system.展开更多
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 m...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.展开更多
文摘Human eye can generally distinguish objects from each other or from their background, if the difference in luminance or color is large. This paper concentrates on the luminance portion and makes an attempt to characterize perception detection to varying contrast which is explained in contrast sensitivity terms. This is accomplished using sinusoidal test patterns. Influence of illumination on perception threshold is also shown in this paper. Practical measurements are done using a calibrated monitor with image capture accomplished with a 1/4' 1.3M camera module system.
文摘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.
