Literature DB >> 20007048

Compress compound images in H.264/MPGE-4 AVC by exploiting spatial correlation.

Cuiling Lan1, Guangming Shi, Feng Wu.   

Abstract

Compound images are a combination of text, graphics and natural image. They present strong anisotropic features, especially on the text and graphics parts. These anisotropic features often render conventional compression inefficient. Thus, this paper proposes a novel coding scheme from the H.264 intraframe coding. In the scheme, two new intramodes are developed to better exploit spatial correlation in compound images. The first is the residual scalar quantization (RSQ) mode, where intrapredicted residues are directly quantized and coded without transform. The second is the base colors and index map (BCIM) mode that can be viewed as an adaptive color quantization. In this mode, an image block is represented by several representative colors, referred to as base colors, and an index map to compress. Every block selects its coding mode from two new modes and the previous intramodes in H.264 by rate-distortion optimization (RDO). Experimental results show that the proposed scheme improves the coding efficiency even more than 10 dB at most bit rates for compound images and keeps a comparable efficient performance to H.264 for natural images.

Year:  2009        PMID: 20007048     DOI: 10.1109/TIP.2009.2038636

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  3 in total

1.  Four-Dimensional Cone-Beam Computed Tomography Image Compression Using Video Encoder for Radiotherapy.

Authors:  Hui Yan; Yexiong Li; Jianrong Dai
Journal:  J Digit Imaging       Date:  2020-10       Impact factor: 4.056

2.  Exploring correlation information for image compression of four-dimensional computed tomography.

Authors:  Hui Yan; Yexiong Li; Jianrong Dai
Journal:  Quant Imaging Med Surg       Date:  2019-07

3.  Evaluation of video compression methods for cone-beam computerized tomography.

Authors:  Hui Yan; Yexiong Li; Jianrong Dai
Journal:  J Appl Clin Med Phys       Date:  2019-05-09       Impact factor: 2.102

  3 in total

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