Jong-bum Choi

Novel context template design scheme for lossless color halftone image compression

A novel template design algorithm is presented for lossless compression of color halftone images. First, we extract the line pattern in the neighbor local region of each bi-level pixel. Then, the representative line pattern is evaluated from these obtained lines, using the least square error minimization. According to the evaluated line pattern and two design constraints, therefore, the context template is shaped. With the designed template, finally, each color channel image is compressed by a context-based binary arithmetic encoder. Based on the adaptiveness of the template to the input image, the proposed templates yield better compression performance than the conventional JBIG templates, which saves 35% of the JBIG bitstream.

Lossless image compression using valley transform

In this paper, a novel geometric transform, called the valley transform (VT), is proposed for robust compression of noisy images. The VT employs a nonlinear transform to convert random signals into regular ones. The proposed VT is able to change random pixels to regular one. For testing the compression performance, the VT is combined with the SPHIT method. The VT yields slightly better performance than the conventional image codecs such as JBIG, HD-photo and H.264 intra method in the lower bit-plane image compression.