An Extensive Analysis of Digital Image Compression Techniques Using Different Image Files and Color Formats
Data storage on the device can affect the access speed of the device used; for example, files, images, and data will affect the performance of the device, become slow to access, difficult to open, download, and save images, files, because the available storage capacity is limited, with the problems...
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Published in | International journal on advanced science, engineering and information technology Vol. 13; no. 5; pp. 1971 - 1977 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
31.10.2023
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Online Access | Get full text |
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Summary: | Data storage on the device can affect the access speed of the device used; for example, files, images, and data will affect the performance of the device, become slow to access, difficult to open, download, and save images, files, because the available storage capacity is limited, with the problems that arise, an image compression technique is needed to minimize storage space and speed up the access. The compression technique can reduce a file, image, and data size but does not reduce the existing image's quality or lower the threshold during the sending or receiving. This research aims to reduce the size, speed up the process of accessing data on devices, and, more importantly, minimize memory space. It can also affect the bandwidth used when sending and receiving files and can speed up the process of sending from source to destination. The method used in this study is Lossy Compression, lose less Compression by comparing RLE, Huffman, and LZW using different image file types. For the Lossless Technique, the best quality reduction ratio is in binary image types, whether using a background or not using a background. The best results obtained are 99.10% (PNG Compression). Using the BMP file extension type, the recommended reduced ratio is lossy compression with format image BMP (JPG compression) for binary image using Lossless Compression has a good reduced ratio compression with an average of 99%. |
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ISSN: | 2088-5334 2088-5334 |
DOI: | 10.18517/ijaseit.13.5.19319 |