An Enhanced Lossless Image Compression Based on Hierarchical Prediction Context Adaptive Coding

To display high bit resolution images on low bit resolution displays, bit resolution needs to be reduced. Towards achieving a reduced bit rates and high compression gain, an enhanced method for compression of various color images are presented, which is based on hierarchical prediction and adaptive coding. An RGB image is first transformed to YCbCr by a reversible color transform and a various conventional lossless grayscale image compression techniques which encodes Y component. A hierarchical decomposition that enables the use of upper pixels, left pixels, and lower pixels for the pixel prediction to encode the chrominance channel. The prediction error is measured based on context model and the adaptive coding is applied to the error signal. Parameters such as peak signal to noise ratio, encoding, decoding time and bit rate have been evaluated and it is exposed that the proposed method further reduces the bit rates compared with JPEG2000 and CALIC. Keywords-Context adaptive arithmetic coding, Hierarchical decomposition,Lossless RGB image compression, Pixel prediction, Reversible color transform.