Image Binarization and Lossless Compression of Ancient Documents using SPIHT Algorithm

Abstract

The ancient documents provides huge amount of information about the past, inventions and manuscripts which should be protected cautiously. These documents store a noteworthy amount of human heritage over time. However, many environmental factors which degrade the documents severely. A key step in all image processing is image binarization. Here the image is binarized using the gradient information including the phase feature. The three main steps are: preprocessing, image binarization, postprocessing. In the preprocessing step, both adaptive median filter and iterative wiener filter used to remove the noise from the image. In the postprocessing step, the BDND (Boundary Discrimination Noise Detection) filter is used to determine whether the current pixel is corrupted or not and the ABF (Adaptive Bilateral Filter) is used to sharpens the edge. For further image enhancement, the CLAHE (Contrast Limited Adaptive Histogram Equalization) is used to enhance the contrast of the input image. Finally, the binarized output need to be stored in effective manner but it consumes large amount of space and takes more number of bits to transfer from one place to another. So, the SPIHT (Set Partitioning in Hierarchical Tree) algorithm with Huffman Coding is used for lossless image compression, saves more number of bits to be transferred and provides enhanced image quality.