Abstract:
Image compression has highly developed in recent decades. The common way is to transform the sensed image into an appropriate basis, then encode the important coefficient...Show MoreMetadata
Abstract:
Image compression has highly developed in recent decades. The common way is to transform the sensed image into an appropriate basis, then encode the important coefficients to reduce the data size. The Compressive Sensing based imaging (CSI) system can combine sensing and source coding process in one step. It is clear that the CSI system has the compression property, but compression of the CSI does not have the conventional meaning. Sometimes CSI measurements even require a larger memory size than the recovered image. In order to improve the data compression property of the CSI system, a lossy quantization mechanism for CSI method is proposed instead of employing the uniform quantizer with a fixed precision. The mechanism is easy to implement and has small distortion. In terms of recovery quality the improvement presents good data compression.
Date of Conference: 05-07 July 2017
Date Added to IEEE Xplore: 23 October 2017
ISBN Information: