Lossless Image Compression Using Pixel Reordering

Lossless image compression techniques typically consider images to be a sequence of pixels in row major order. The processing of each pixel consists of two separate operations. The first step forms a prediction as to the numeric value of the next pixel. Typical predictors involve a linear combination of neighboring pixel values, possibly in conjunction with an edge detection heuristic. In the second step, the difference between that prediction and the actual value of the next pixel is coded. In high-performance mechanisms such as JPEG-LS, the error differential is coded in a conditioning context established by a possiblydifferent set of neighboring pixels. A per-context arithmetic, minimum-redundancy, or Rice coder completes the processing of each pixel. In this paper we explore pixel reordering as a way of reducing the start-up (or learning) cost associated with each context. By permuting the prediction errors into an order that reflects the assessed volatility of the conditioning co...

• Type: Conference
• Year: 2004
• Where: ACSC
• Authors: Michael Ciavarella, Alistair Moffat
• Keywords: ACSC 2004, Conditioning Context, Lossless Image Compression, Pixel, Theoretical Computer Science