Improved Golomb Code for Joint Geometric Distribution Data and Its Applications in Image Processing
نویسندگان
چکیده
Golomb coding is a special case of Huffman coding that is optimal for the data with geometric progression distribution probability. In this paper, we will generalize the Golomb coding by joint probability. In image progression, there are many conditions that the probability of a data not only has geometric distribution probability but also depends on another data. (For example, the difference between the intensities of two pixels is highly dependent on their distance) Based on the requirement, we improve the Golomb codes by considering the joint probability and make Golomb coding more flexible and efficient. The proposed modified Golomb codes will be useful in digital signal and image processing. For example, after performing the DCT, we can use the high correlation between the average amplitudes of low frequency components and middle frequency components to improve the compression ratio by the proposed coding scheme.
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تاریخ انتشار 2010