Finding faces in wavelet domain for content-based coding of color images: two approaches

2000 ◽  
Author(s):  
Jayashree Karlekar ◽  
U. B. Desai
Keyword(s):  
Color Images ◽  
Wavelet Domain

A New Robust Reversible Blind Watermarking in Wavelet-Domain for Color Images

2016 ◽  
Vol 16 (02) ◽  
pp. 1650006 ◽  
Author(s):  
P. Manimehalai ◽  
P. Arockia Jansi Rani
Keyword(s):  
Clustering Algorithm ◽  
Color Image ◽  
Reversible Watermarking ◽  
Color Images ◽  
Blind Watermarking ◽  
Wavelet Domain ◽  
Wavelet Coefficients ◽  
Recovered Image ◽  
Host Image

Reversible watermarking methods are used for copyright protection and are able to recover the host image without distortion. Robust reversible watermarking technique should resist against intentional and unintentional image processing attacks. Robust reversible watermarking techniques should have three features namely imperceptibility, reversibility and robustness. In this paper, it is proposed to develop a new robust reversible blind watermarking for color images based on histogram construction of the wavelet coefficients constructed from the cover image. In the proposed approach, the red component of a host color image is decomposed into wavelet coefficients. Motivated by the excellent spatio-frequency localization properties of wavelets, this technique is proposed in the wavelet domain. The pixels are adjusted before watermark embedding such that both overflow and underflow of pixels during embedding is avoided and image is recovered without distortion. Based on histogram construction and the local sensitivity of Human Visual System (HVS) in wavelet domain, the watermark is embedded. For watermark extraction without host image, k-means clustering algorithm is proposed. The experimental results show that the proposed technique has good performance in terms of reversibility and robustness with the high quality of the watermarked image. The PSNR value of the recovered image is around 48[Formula: see text]dB which proves that the quality of the recovered image is not degraded.

scholarly journals Image Denoising in Wavelet Domain with Filtering and Thresholding

2018 ◽  
Vol 7 (3.34) ◽  
pp. 327
Author(s):  
K Sumathi ◽  
Ch Hima Bindu
Keyword(s):  
Mutual Information ◽  
Image Denoising ◽  
Gaussian Noise ◽  
Color Images ◽  
Wavelet Domain ◽  
Wavelet Coefficients ◽  
Noisy Images

In this paper, the proposed method is implemented for removal of salt & pepper and Gaussian noise of black & white & color images toacquire the quality output. In this work initially wavelet coefficients are extracted for noisy images. Later apply denoise filteringtechnique on the high transform sub bands of noisy images (either color/ B & W) using new laplacian filters with 4 directions. Finallythreshold of an image is generated to extract denoisy coefficients. At last inverse of above subband coefficients can give denoise imagefor further processing. The proposed method is verified against various B & W/color images and it gives a better PSNR (Peak Signal toNoise Ratio) & MI (Mutual Information). These values are compared with different noise densities and analyzed visually.

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