Suppressing Shot Noise Using Quadratic Variable Step-Size Quantization for the Initial Acquisition of Camera-Raw Image Data.

Abstract

Digital images from today's premium digital cameras have a higher dynamic range than what humans can perceive. Maximumly keeping the image information captured by sensors while reducing the file size of the output raw image data is highly desirable. In this paper, we show that the extractable image information contained in high-quality HDR images taken by premium cameras can be preserved using a bit-depth of only 8 to 9 bits/pixel when the shot-noise-introduced extra entropy is suppressed. The quadratic variable step-size quantization is used to suppress the shot-noise-introduced entropy. The ratio of the quantization step-size of the quadratic quantizer over the shot noise amplitude is introduced as a parameter to measure the relative quantization noise level, and is used to design the quadratic quantizers that maximally suppress the shot noise. Finally, quadratically quantized real CFA camera-raw image data are losslessly compressed. Compared with the lossless compression on linearly quantized data, at least more than 50% bitrate savings are achieved. Such high bitrate savings without loss of extractable image information are very attractive. Thus, it is highly worthwhile to explore, in the future, hardware implementations of quadratic quantization in image sensors.