{"title":"图像压缩和传输中的修正小波差分缩减法性能分析","authors":"T. S. Bindulal","doi":"10.21833/ijaas.2023.10.025","DOIUrl":null,"url":null,"abstract":"The wavelet difference reduction (WDR) method, a variant of run-length coding, finds its significance in data transmission applications. Over time, numerous enhanced iterations of WDR methods have emerged. Notably, the Adaptive Scalable WDR method exhibits superior coding gains, as evidenced by the peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM), when compared to its predecessors. This paper conducts an exhaustive examination, encompassing both coding performance and time complexity, of various WDR methods vis-à-vis the conventional image compression algorithm SPIHT. Furthermore, it delves into the performance assessment of diverse coding techniques in the realm of encoding arbitrary-shaped objects. The analysis underscores that modified WDR variants demonstrate remarkable prowess in compression, rendering them invaluable for rapid transmission in bandwidth-constrained networks. To substantiate these findings, coding results (measured in terms of PSNR) are derived from the application of these algorithms to standard test images, MRI images, and video still images. The results reveal coding gains ranging from 0.5 dB to 1 dB for regular resolution images and a substantial 2 dB to 12 dB for scalable resolution scenarios, in comparison to traditional coding approaches. Consequently, this analysis underscores the convenience and superiority of modified WDR methods, not only for still images but also for encoding and transmitting arbitrary-shaped objects.","PeriodicalId":46663,"journal":{"name":"International Journal of Advanced and Applied Sciences","volume":"28 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance analysis of modified wavelet difference reduction methods in image compression and transmission\",\"authors\":\"T. S. Bindulal\",\"doi\":\"10.21833/ijaas.2023.10.025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The wavelet difference reduction (WDR) method, a variant of run-length coding, finds its significance in data transmission applications. Over time, numerous enhanced iterations of WDR methods have emerged. Notably, the Adaptive Scalable WDR method exhibits superior coding gains, as evidenced by the peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM), when compared to its predecessors. This paper conducts an exhaustive examination, encompassing both coding performance and time complexity, of various WDR methods vis-à-vis the conventional image compression algorithm SPIHT. Furthermore, it delves into the performance assessment of diverse coding techniques in the realm of encoding arbitrary-shaped objects. The analysis underscores that modified WDR variants demonstrate remarkable prowess in compression, rendering them invaluable for rapid transmission in bandwidth-constrained networks. To substantiate these findings, coding results (measured in terms of PSNR) are derived from the application of these algorithms to standard test images, MRI images, and video still images. The results reveal coding gains ranging from 0.5 dB to 1 dB for regular resolution images and a substantial 2 dB to 12 dB for scalable resolution scenarios, in comparison to traditional coding approaches. Consequently, this analysis underscores the convenience and superiority of modified WDR methods, not only for still images but also for encoding and transmitting arbitrary-shaped objects.\",\"PeriodicalId\":46663,\"journal\":{\"name\":\"International Journal of Advanced and Applied Sciences\",\"volume\":\"28 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Advanced and Applied Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21833/ijaas.2023.10.025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advanced and Applied Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21833/ijaas.2023.10.025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
小波差分缩减法(WDR)是运行长度编码的一种变体,在数据传输应用中具有重要意义。随着时间的推移,出现了许多小波差分迭代增强方法。值得注意的是,自适应可扩展 WDR 方法与前几种方法相比,在峰值信噪比(PSNR)和结构相似性指数指标(SSIM)方面表现出更高的编码效率。本文对各种 WDR 方法与传统图像压缩算法 SPIHT 的编码性能和时间复杂性进行了详尽的研究。此外,它还深入研究了各种编码技术在编码任意形状物体方面的性能评估。分析结果表明,经过改进的 WDR 变体在压缩方面表现出卓越的能力,使其在带宽受限的网络中进行快速传输时变得非常有价值。为了证实这些发现,我们将这些算法应用于标准测试图像、核磁共振成像图像和视频静态图像,得出了编码结果(以 PSNR 度量)。结果显示,与传统编码方法相比,普通分辨率图像的编码增益从 0.5 dB 到 1 dB 不等,而可扩展分辨率场景的编码增益则高达 2 dB 到 12 dB。因此,这项分析强调了修改后的 WDR 方法的便利性和优越性,不仅适用于静态图像,也适用于编码和传输任意形状的物体。
Performance analysis of modified wavelet difference reduction methods in image compression and transmission
The wavelet difference reduction (WDR) method, a variant of run-length coding, finds its significance in data transmission applications. Over time, numerous enhanced iterations of WDR methods have emerged. Notably, the Adaptive Scalable WDR method exhibits superior coding gains, as evidenced by the peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM), when compared to its predecessors. This paper conducts an exhaustive examination, encompassing both coding performance and time complexity, of various WDR methods vis-à-vis the conventional image compression algorithm SPIHT. Furthermore, it delves into the performance assessment of diverse coding techniques in the realm of encoding arbitrary-shaped objects. The analysis underscores that modified WDR variants demonstrate remarkable prowess in compression, rendering them invaluable for rapid transmission in bandwidth-constrained networks. To substantiate these findings, coding results (measured in terms of PSNR) are derived from the application of these algorithms to standard test images, MRI images, and video still images. The results reveal coding gains ranging from 0.5 dB to 1 dB for regular resolution images and a substantial 2 dB to 12 dB for scalable resolution scenarios, in comparison to traditional coding approaches. Consequently, this analysis underscores the convenience and superiority of modified WDR methods, not only for still images but also for encoding and transmitting arbitrary-shaped objects.