A study of Performance Analysis of Image Compression Methods and Denoising Natural Image

Sarkar, Md. Ashikur Rahman; Hasan, Md. Mahmudul; Khalek, Md. Abdul

dc.contributor.author	Sarkar, Md. Ashikur Rahman
dc.contributor.author	Hasan, Md. Mahmudul
dc.contributor.author	Khalek, Md. Abdul
dc.date.accessioned	2013-01-24T06:43:00Z
dc.date.accessioned	2019-06-10T09:21:52Z
dc.date.available	2013-01-24T06:43:00Z
dc.date.available	2019-06-10T09:21:52Z
dc.date.issued	2012-08
dc.identifier.uri	http://hdl.handle.net/20.500.11948/854
dc.description.abstract	Image compression is in high demand as it reduces the computational time and consequently the cost in image storage and transmission. The basis for image compression is to remove redundant and unimportant data while to keep the compressed image quality in an acceptable range. Image compression is an application of data compression on digital images which is in highly demand as it reduces the computational time and consequently the cost in image storage and transmission. Wavelet Transform (WT) is used for compressing a natural image, De noise. Several wavelets (Haar, Daubechies, Coiflet, Symmlet and Demy) are used for compressing and Denoising image. As a measure of performance Root Mean Square Error (RMSE), Peak Signal to Noise Ratio (PSNR), Compression Ratio (CR) are calculated between the original and compressed images. It is observed from our study that Haar performs better (lowest RMSE, highest PSNR and CR) than any other tested wavelets for natural Image. JPEG compression method performs 48.85% better than Haar wavelet	en_US
dc.language.iso	en	en_US
dc.publisher	Daffodil International University	en_US
dc.relation.ispartofseries	p03027;
dc.subject	Analysis of image compression	en_US
dc.title	A study of Performance Analysis of Image Compression Methods and Denoising Natural Image	en_US
dc.type	Thesis	en_US