A Study on Data Compression Using Image Sets and Ambiguous Entropy

点击翻译按钮获取中文摘要

Information in two-dimension digital monochromatic image can be considered to be a mapping function from the domain of pixels into the region of the intensity at contrast. It usually shows by the matrix expression. It can be thought that the image encoding such as JPEG has achieved the information compression by concisely expressing the approximation type. The image encoding method proposed by this research handles data within the range of the intensity in each pixel of the original image which has the upper bound and the lower bound. It has features such as suiting the object encoding, being able to use the set operations, being able to treat the level of the quality quantitatively and systematically. by using the concept of ambiguous information, and being able to reproduce the image based on a preferable criterion during the renewal processing.In this report, the classes of the objects adopt the smooth figure where smooth area is expressed, the edge figure where boundary of an object is identified, and the one-dimension scanning figure which is not depending on the kind of pictures and can be applied to arbitrary domains. The image compression and the reconstruction were tried to various images like a natural image and an illustration image with monochromatic or e color, and the advantage and the fault of the proposed method were investigated in detail. In the color image, we separate the plains by using the YUV table color system which are mutually independent. This encoding and decoding process are performed to each, and the constructed picture is compounded. It is able to be confirmed that the above-mentioned features functioned effectively as the result of various experiments. However, there is a fault that the compressibility is inferior compared with JPEG in natural images. As future improvements it is necessary to add the new object classes and to devise the mode of the color image expression.