Context-Based Lossless Compression of Mosaic Image with Bayer Pattern

Author

Cheng, Yongqiang ; Xie, Keming ; Zhang, Gang

Author_Institution

Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan

Volume

1

fYear

2008

fDate

27-30 May 2008

Firstpage

481

Lastpage

485

Abstract

In this paper, a predictive model for compression of mosaic image with Bayer pattern is proposed. It consists of TFNN neural network predictor and adaptive correction part based on context. As in JPEG-LS, the adaptive part of the predictor is context-based and it is used to ldquocancelrdquo the integer part of the offset due to the TFNN predictor. In the meantime, we propose a context quantization approach that achieves high coding efficiency. Compared with existing methods of CFA image lossless compression, the performance of proposed method is apparently the best.

Keywords

data compression; image coding; image colour analysis; image segmentation; neural nets; optical filters; Bayer pattern; JPEG-LS; TFNN neural network predictor; adaptive correction; coding efficiency; context quantization approach; context-based lossless compression; mosaic image; Color; Image coding; Image converters; Image generation; Image storage; Interpolation; Predictive models; Quantization; Sensor arrays; Wavelet packets; Bayer pattern; compression; mosaic image;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing, 2008. CISP '08. Congress on

Conference_Location

Sanya, Hainan

Print_ISBN

978-0-7695-3119-9

Type

conf

DOI

10.1109/CISP.2008.101

Filename

4566202