Catadioptric images compression using an adapted neighborhood and the shape-adaptive DCT

In the catadioptric images, the neighborhood topology is usually modified by the mirror shape which consists of significant radial distortions and low non-uniform resolution because of its convexity geometry. Consequently, conventional compression approaches (i.e. H.264 intra-frame coding or JPEG standard) based on rectangular block partitioning cannot be applied directly to catadioptric images because they inevitably produce significant block effects. In this investigation, we propose a new coding scheme based on an adaptive block partitioning. Particularly, to reduce the blocking artifacts, we propose the shape-adaptive discrete cosine transform (SA-DCT) and adapted neighborhood. The adapted neighborhood is obtained from the equivalence between the catadioptric image and the scene point’s projection on the unit sphere. The adapted blocks shape correctly follows the geometric context and varies according to the resolution of the catadioptric images. Such changes improve considerably the compression efficiency using the block partitioning in catadioptric images. Experimental results figured out that our proposal scheme outperforms the JPEG standard and the Intra-frame coder H264. Moreover the proposed coding scheme based on SA-DCT transform and the suitable partitioning for catadioptric images provides high PSNR and a considerable reduction of block effects compared to conventional approaches, especially in the case of low bit rate.