Computer Science & Engineering

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Browsing Computer Science & Engineering by Subject "Compression"

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    A Simplified Fractal Texture Analysis Approach using Quadtree Decomposition with Huffman Coding Technique 2021 September
    (Middle East Journal of Applied Science & Technology, 2021) Jacob, Rani
    Fractal compression is compression of the lossy type, which is applied for natural textured images. A fractal image compression technique based on the Quadtree algorithm and Huffman coding is proposed in this work. Agonizingly, the term "fractal compression" refers to an image compression technique that uses the fractal geometry of the image data stream to achieve lossy compression. Realistic images and textures are created with the help of this tool. It is based on the fact that parts of an image are frequently similar to other parts of the same image, which allows for faster processing. The most widely used partitioning mechanism is image partitioning in a tree structure. In this emerging world of image processing, quad tree partitioning is a one-of-a-kind technique that divides an image into a set of homogeneous regions. Huffman coding is a type of data compression that is lossless. The Huffman encoding algorithm is introduced through this technique, which creates an alphabetic list of all of the alphabet symbols, which is then arranged in descending order of their likelihood of occurring. The peak signal-to-noise ratio is quite improved by employing the proposed technique, and the encoding time is reduced.
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    An Efficient Analysis of Wavelet Techniques on Image Compression
    (Irish Interdisciplinary Journal of Science & Research (IIJSR), 2022) Jacob, Rani
    Compression can be defined as an art form that involves the representation of information in a reduced form when compared to the original information. Image compression is extremely important in this day and age because of the increased demand for sharing and storing multimedia data. Compression is concerned with removing redundant or superfluous information from a file to reduce the size of the file. The reduction of the file size saves both memory and the time required to transmit and store data. Lossless compression techniques are distinguished from lossy compression techniques, which are distinguished from one another. This paper focuses on the literature studies on various compression techniques and the comparisons between them.
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    Performance Analysis of Image Compression in MRI BI using ROI & Non ROI coding technique
    (International Journal of Advanced in Management, Technology and Engineering Sciences, 2022) Jacob, Rani
    The growing demand for medical image storage and transmission has resulted in a shortage of memory and bandwidth. Compression was used to find these issues. Clinical image compression is used to improve image quality, reduce bit rate, increase compression efficiency for storage and transmission, and reduce cost. MRI images are quite clinical. To store and transmit thousands of MRI pictures, you need a lot of storage space and bandwidth. Thus, high-quality MRI image compression is more research focused. Many Compression strategies for MRI with low compression rate cause loss of data on lesions, and lead to misdiagnose. This research proposed several MRI image compression methods. Our main goals are to provide more compressed clinical images, encourage early location and finding followed by therapy using multi-resolution compression technology. A two-dimensional (2D) picture arrangement is created by first converting 3D MRI scans into 2D images. Then range and area blocks are arranged by 3D object's spatio-temporal similarity. In addition, the proposed technique uses wavelet transform and MRG algorithm to analyse the performance of wavelet contains transformation, quantization, and entropy coding to compress the most significant piece of ROI using DWT and s. It compresses non-ROI using DCT and MHE (merging based Huffman encoding). Finally, residual compensation is used to provide good decompression quality MRI compression.