Lossy and lossless compression for color-quantized images

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
Pages870-873
Volume1
Publication statusPublished - 2001

Publication series

Name
Volume1

Conference

TitleIEEE International Conference on Image Processing (ICIP) 2001
PlaceGreece
CityThessaloniki
Period7 - 10 October 2001

Abstract

An efficient compression scheme for color-quantized images based on progressive coding of color information has been developed. Rather than sorting color indexes into a linear list structure, a binary-tree structure of color indexes is proposed. With this structure the new algorithm can progressively recover an image from 2 colors up to all of the colors contained in the original image, i.e., a lossless recovery achieved. Experimental results show that it can efficiently compress images in both lossy and lossless cases. Typically for color-quantized Lena image with 256 colors, the algorithm achieved 0.5 bpp lower than state-of-the-art lossless compression methods while preserving the efficient lossy compression. Such a compression scheme is very attractive to many applications that require the ability to fast browsing or progressive transmission, and if necessary, to exactly recover the original image.

Citation Format(s)

Lossy and lossless compression for color-quantized images. / Chen, X.; Feng, J.; Kwong, S.
IEEE International Conference on Image Processing. Vol. 1 2001. p. 870-873.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review