Scalable reduced dimension object segmentation based adaptive progressive color-image coding

A fast and efficient wavelet image-coding algorithm based on scalable reduced dimension object segmentation (SRDOS) introduced in [1] is presented in this paper. Object will be segmented right after wavelet transform with lifting scheme. It is the reduced dimension space of the transform domain in which SRDOS algorithm is applied to detect and segment the object with lower complexity and more sufficient accuracy. Since its characteristics of multi-scale segmentation and higher performance/complexity, SRDOS adapts to object-oriented adaptive progressive wavelet color-image coding. For higher compression ratio, coding algorithm takes advantage of the relationship of the same spatial location at the same scale to remove spatial redundancy of the landscape orientation and applies context-based arithmetic coding algorithm to reduce spatial redundancy of the vertical orientation. For keeping more important information, object and non-object will have different quantizers and priorities respectively. The experiments show that SRDOS based coding algorithm gains higher subject visual quality and image peak signal to noise ratio (ISNR).