Near lossless coding of sparse histogram images based on zero-skip quantization

Abstract

This paper introduces a zero-skip quantization (ZS.Q) scheme for the near lossless coding of sparse histogram images. Increases in the range of pixel values and various tone mapping operations on those pixel values mean that the histogram bins often contain no pixels. Recently, this sparseness of the histogram was used to increase the lossless coding performance by introducing histogram packing. This approach was extended to lossy coding by combining spatial quantization and lossless coding. However, such methods do not satisfy the near lossless (NL) condition. In contrast, conventional NL coding such as the JPEG-LS standard satisfies the NL condition, but does not use the histogram sparseness. In this paper, a simple ZS.Q procedure is introduced that uses the histogram sparseness to increase coding efficiency under the NL condition. The proposed method has the following advantages: 1) It guarantees the maximum quantization error is less than some threshold; 2) It can be combined with an arbitrary lossless encoder, such as lossless JPEG 2000 or lossless JPEG-LS; 3) Coding errors do not accumulate under repeat encoding and decoding.