CS与JPEG图像压缩性能的比较

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

摘要翻译：
本文对JPEG和压缩感知两种方法进行了比较。从图像压缩的角度对这两种方法进行了比较。通过测量图像质量与用于图像恢复的样本数进行比较。图像在视觉上进行了比较。同时，对两种方法的数值质量值PSNR进行了计算和比较。实验结果表明，与JPEG压缩下的图像相比，压缩感知方法恢复的图像具有更高的PSNR值。在具有少量细节的灰度图像中，差异更大，例如医学图像（X射线）。理论得到了实验结果的支持。
---
英文标题：
《Comparison between CS and JPEG in terms of image compression》
---
作者：
Danko Petric, Marija Milinkovic
---
最新提交年份：
2018
---
分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Image and Video Processing        图像和视频处理
分类描述：Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.
用于图像、视频和多维信号的形成、捕获、处理、通信、分析和显示的理论、算法和体系结构。感兴趣的主题包括：数学，统计，和感知图像和视频建模和表示；线性和非线性滤波、去模糊、增强、恢复和重建退化、低分辨率或层析数据；无损和有损压缩编码；分割、对齐和识别；图像渲染、可视化和打印；计算成像，包括超声、断层和磁共振成像；以及图像和视频的分析、合成、存储、搜索和检索。
--
一级分类：Computer Science        计算机科学
二级分类：Multimedia        多媒体
分类描述：Roughly includes material in ACM Subject Class H.5.1.
大致包括ACM学科类H.5.1中的材料。
--

---
英文摘要：
  The comparison between two approaches, JPEG and Compressive Sensing, is done in the paper. The approaches are compared in terms of image compression. Comparison is done by measuring the image quality versus number of samples used for image recovering. Images are visually compared. Also, numerical quality value, PSNR, is calculated and compared for the two approaches. It is shown that images, recovered by using the Compressive Sensing approach, have higher PSNR values compared to the images under JPEG compression. Difference is larger in grayscale images with small number of details, like e.g. medical images (x-ray). The theory is supported by the experimental results.
---
PDF链接：
https://arxiv.org/pdf/1802.05114

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏0 回帖

关键词：JPEG JPE PEG Presentation Architecture PSNR 方法 Sensing 医学 done