Zone Based Lossy Image Compression Using Discrete Wavelet and Discrete Cosine Transformations
| Autor: | Muhammad Adil Abid, Khalid Iqbal, Naeem Iqbal, Nafees Ahmad, Lansheng Han |
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| Rok vydání: | 2019 |
| Předmět: |
Lossless compression
business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Data compression ratio Data_CODINGANDINFORMATIONTHEORY computer.file_format JPEG JPEG 2000 Compression ratio Discrete cosine transform Computer vision Artificial intelligence business computer Volume (compression) Image compression |
| Zdroj: | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030213725 |
| DOI: | 10.1007/978-3-030-21373-2_62 |
| Popis: | Due to the huge volume of image data generation in numerous domains, image compression has got the attention of researchers to minimize redundant image contents for efficient handling and transmission. However, a small region of interest (ROI) in the whole image is a major challenge in image compression. In this perspective, lossless image compression techniques have a low compression rate, and lossy image compression approaches, like JPEG, JPEG2000 and HD Photo, slightly loose data with high compression ratio. High compression ratio of lossy image compression helps in saving storage and fast transfer of data. In this paper, we proposed new DWT based zoning technique in combination with DCT for image compression. DWT divides an image into LL, LH, HL and HH frequencies and Zoning is further dividing these images into four parts as an input to DCT one after another. The output of DCT on each zone is then combined into a compressed bitstream image. Extensive experimentation is performed on various common images to compare the results with JPEG, JPEG2000 and HD Photo methods. Our ZDD methods remarkably performed better than the aforementioned techniques. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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