Lossless Compression for Compound Documents Based on Block Classification?

Image and video compressions are required to reduce the number of bits needed to represent the content of the original data. Compression of scanned or compound documents and images can be more difficult than the original data because it is a mixture of text, picture and graphics. The main requirement of the compound document or images is quality of the decompressed data. Here Quality is defined as the achievement of the high compression ratio. The degradation of compound image or document compression is based on storage and the transmission of the document. Reduce the storage size and the lossless quality are challenging task. In this proposed method a block-based compression method used for scanned documents (and also video). This paper presents the study on the implementation of Mat lab based on pattern matching algorithm. A high-quality document compressor even with single and multipage document is known as H.264/advanced video coding (AVC). The segmented blocks of data are inputs. Each block is matched to our previous pattern. Then the method H.264/AVC uses the Integer transform to convert resulting is encoded using CABAC. The compressed image or scanned documents are visually lossless with high compression ratio (compare to previous standards). We now describe the desired features and how one can implement them using AVC. The proposed Encoder is more efficient for transform encoding of the residual data.