Lossless image compression is used for reducing the volume of image data without compromising the data quality. The aim is to reduce the demand on processors and to increase the speed at which images can be compressed. LOCO-R algorithm is used for image compression. It is based on the LOCO-I (Low complexity Lossless Compression for image) algorithm. The LOCO-R algorithm has already been implemented for image with 8-bit pixel values. In this paper, we proposed the LOCO-R algorithm for 16 bit image; it reduces the implementation complexity and reduced the compression ratio. This algorithm is based on prediction and context models; the model is tuned for efficient performance in conjunction with a collection of Huffman codes, which realized with Golomb-Rice code.

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Lossless Image Compression Huffman Coding Context Prediction method