Biomedical Image Processing with Improved SPIHT Algorithm and optimized Curvelet Transform Technique
| Autor: | B Anish Fathima, M Mahaboob, L Jubair Ahmed, B Gokulavasan |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies Pattern recognition Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology Image (mathematics) Support vector machine Set partitioning in hierarchical trees Transformation (function) Computer Science::Computer Vision and Pattern Recognition Encoding (memory) Compression (functional analysis) Compression ratio 0202 electrical engineering electronic engineering information engineering Curvelet 020201 artificial intelligence & image processing Artificial intelligence business 021101 geological & geomatics engineering |
| Zdroj: | 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS). |
| Popis: | The prime idea is to propose an effective compression technique obtaining improved PSNR and better compression ratio (CR) with Curvelet transformation technique and encoding the multi-wavelet parameters using Set Partitioning In Hierarchical Trees (SPIHT) algorithm. Also a comparative study is presented which highlights a dynamic image encoding algorithm against the conventional algorithms such as SVM, EZW & SPECK. Both quantitative and qualitative parameters of algorithm are analyzed for bio-medical images. Analysis inferences represents that the proposed technique treats structures and patterns considerably superior than conventional techniques. |
| Databáze: | OpenAIRE |
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