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Wavelet Transform based Estimation of Images using different Thresholding Techniques

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Sk. Ayesha, M. V. R. Amara Lingeswara Rao, Koteswararao Mallaparapu

Sk. Ayesha, Amara Lingeswara M V R Rao and Koteswararao Mallaparapu. Wavelet Transform based Estimation of Images using different Thresholding Techniques. International Journal of Computer Applications 167(8):20-24, June 2017. BibTeX

	author = {Sk. Ayesha and M. V. R. Amara Lingeswara Rao and Koteswararao Mallaparapu},
	title = {Wavelet Transform based Estimation of Images using different Thresholding Techniques},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {167},
	number = {8},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {20-24},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017914351},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Estimating the images using decimated wavelet transform is very popular technique in different applications. In this paper a new thresholding function with combination of Smoothly Clipped Absolute Deviation (SCAD), Hard thresholding and soft thresholding functions are introduced for wavelet based denoising of images. The proposed technique is applied for denoising of noisy images contaminated with additive white Gaussian noise using Top rule and Visu rule. The results are compared with that of existing SCAD, hard and soft functions denoising method. Root Mean Square Error (RMSE) and Peak Signal to Noise Ratio (PSNR) are used as parameters for testing the quality of denoising.


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Wavelet transform, decimated wavelet transform, image denoising, new thresholding function, top rule, Visu rule.