V. P. S. Thoudam, Tana Sera, Xi Chaow Xi Marak, M. Saddam, Rebecca Lalparmawii
{"title":"低复杂度的16点DCT近似图像压缩","authors":"V. P. S. Thoudam, Tana Sera, Xi Chaow Xi Marak, M. Saddam, Rebecca Lalparmawii","doi":"10.1109/ICCCIS56430.2022.10037721","DOIUrl":null,"url":null,"abstract":"This paper presents an orthogonal multiplier less 16-point DCT transform. The proposed transform was made to have low computational complexity for efficient image compression. The proposed fast transform algorithm has 38 additions and contains no multiplier or bit-shifting. Assessment of the proposed transform was made using computational complexity, and image coding performance measures. The proposed transform has to our best of knowledge the best cost-benefit ratio on comparing with other state of art transform present in literature. The efficiency of the proposed 16-point DCT approximation was evaluated using PSNR and SSIM measurement.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Low complexity 16-point DCT approximation for image compression\",\"authors\":\"V. P. S. Thoudam, Tana Sera, Xi Chaow Xi Marak, M. Saddam, Rebecca Lalparmawii\",\"doi\":\"10.1109/ICCCIS56430.2022.10037721\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an orthogonal multiplier less 16-point DCT transform. The proposed transform was made to have low computational complexity for efficient image compression. The proposed fast transform algorithm has 38 additions and contains no multiplier or bit-shifting. Assessment of the proposed transform was made using computational complexity, and image coding performance measures. The proposed transform has to our best of knowledge the best cost-benefit ratio on comparing with other state of art transform present in literature. The efficiency of the proposed 16-point DCT approximation was evaluated using PSNR and SSIM measurement.\",\"PeriodicalId\":286808,\"journal\":{\"name\":\"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCIS56430.2022.10037721\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCIS56430.2022.10037721","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low complexity 16-point DCT approximation for image compression
This paper presents an orthogonal multiplier less 16-point DCT transform. The proposed transform was made to have low computational complexity for efficient image compression. The proposed fast transform algorithm has 38 additions and contains no multiplier or bit-shifting. Assessment of the proposed transform was made using computational complexity, and image coding performance measures. The proposed transform has to our best of knowledge the best cost-benefit ratio on comparing with other state of art transform present in literature. The efficiency of the proposed 16-point DCT approximation was evaluated using PSNR and SSIM measurement.