Low Complexity Image Compression Algorithm Based on Uniform Quantization of RGB Colour Image for Capsule Endoscopy
| Autor: | Nithin Varma Malathkar, Surender Kumar Soni |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Lossless compression
Pixel Computational complexity theory Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Data_CODINGANDINFORMATIONTHEORY computer.file_format Golomb coding Compression ratio Code (cryptography) RGB color model Computer vision Artificial intelligence Pulse-code modulation business computer |
| Zdroj: | Communications in Computer and Information Science ISBN: 9789811331398 |
| DOI: | 10.1007/978-981-13-3140-4_21 |
| Popis: | Demand for wireless capsule endoscopy is increasing rapidly due to its simplicity and comfortable procedure. However, the wireless capsule endoscopy lack in complete diagnosing of gastrointestinal tract due to its limited power supply and size. Low complexity image compression algorithm plays vital role in saving power and size by reducing the data as transmitter consume 60% of capsule power. A high efficiency and lossless image compression algorithm is proposed, which is a combination of uniform quantization, simple predictive coding and Golomb Rice code. In the proposed algorithm, RGB colour image is quantized using uniform quantization. Then, differential pulse code modulation is applied, where current pixel value is subtracted with previous pixel value to provide a difference error value. The difference error value is encoded using Golomb Rice code. Several endoscopic images are considered for evaluating the performance and efficiency of proposed algorithm. The proposed algorithm provided the compression ratio of 72.5 with less computational complexity and memory usage. |
| Databáze: | OpenAIRE |
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