Lossless compression of pre-press images using linear color decorrelation

Abstract

Summary form only given. In the pre-press industry color images have both a high spatial and a high color resolution. Such images require a considerable amount of storage space and impose long transmission times. Data compression is desired to reduce these storage and transmission problems. Because of the high quality requirements in the pre-press industry only lossless compression is acceptable. Most existing lossless compression schemes operate on gray-scale images. In this case the color components of color images must be compressed independently. However, higher compression ratios can be achieved by exploiting inter-color redundancies. We present a new technique for exploiting inter-component redundancies. The technique is based on a modified Karhunen-Loeve transform (KLT) scheme in combination with a novel quantization scheme that guarantees losslessness. The KLT decorrelates the color components. It is recomputed on a block by block basis and is therefore spatially adaptive. Spatial redundancies are removed using predictive techniques (lossless JPEG predictor no. 7 and the CALIC-predictor). The data which remains after the (spatial and color) decorrelation should be entropy-coded, but in the current implementation of our scheme only the entropy of the remaining data is computed. Note that in each block some block-dependent information must be sent, such as entropy-coder initialization information and KLT-descriptors (i.e., the rotation angles of the orthogonal KLT-matrix).