Abstract
Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression.
Highlights
With the most challenging area in computer animations and multimedia technology, data compression remains a key issue regarding the cost of storage space and transmission times
We present various approaches for reducing encoding time for the image as well as video fractal coding
In circular prediction mapping and non-contractive inter-frame mapping, each range block is motion compensated by a domain block in the previous frame, which is of the same size as the range block even though the domain block is always larger than the range block in conventional fractal image codec
Summary
With the most challenging area in computer animations and multimedia technology, data compression remains a key issue regarding the cost of storage space and transmission times. Though the Fractal coding is advantageous with respect to the compression ratio and image reconstruction quality, but it has the heavier non-acceptance related to the time elapsed for the check of similarity. It is suitable for the gray level image compression, but later some new techniques were developed for the color image/video compression. Image compression with finite automata can be applied to digital video sequences, which are typically represented by a series of frames or digital images [5]. International Journal of Interactive Multimedia and Artificial Intelligence, Vol 4, No2
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