A new approach to invisible water marking of color images using alpha blending

2018 ◽  
Author(s):  
Anirban Patra ◽  
Arijit Saha ◽  
Ajoy Kumar Chakraborty ◽  
Kallol Bhattacharya
Keyword(s):  
Color Images ◽  
New Approach

New approach to metamerism measurement on halftone color images

Measurement ◽  
2011 ◽  
Vol 44 (8) ◽  
pp. 1441-1447 ◽  
Author(s):  
Igor Zjakic ◽  
Djurdjica Parac-Osterman ◽  
Irena Bates
Keyword(s):  
Color Images ◽  
New Approach

New approach to palette selection for color images

1991 ◽  
Author(s):  
Raja Balasubramanian ◽  
Jan P. Allebach
Keyword(s):  
Color Images ◽  
New Approach ◽  
Selection For

scholarly journals QualityAdaptive sharpness enhancement and noise removal of a colour images based on the bilateral filtering

2012 ◽  
pp. 49-55
Author(s):  
V. Durgarchana ◽  
B. Praveen ◽  
B. Sridhar
Keyword(s):  
Bilateral Filter ◽  
Noise Removal ◽  
Color Images ◽  
Experimental Results ◽  
Perceptual Quality ◽  
Bilateral Filtering ◽  
New Approach ◽  
Unsharp Mask ◽  
Sharpness Enhancement ◽  
Restoration Algorithms

In this paper, we present the Adaptive Bilateral Filter (ABF) for sharpness enhancement and noise removal of a colour images. The ABF sharpens an image by increasing the slope of the edges without producing overshoot or undershoot. It is an approach to sharpness enhancement that is fundamentally different from the unsharp mask (USM). This new approach to slope restoration also differs significantly from previous slope restoration algorithms. Compared with an USM based sharpening method, the optimal unsharp mask (OUM), In terms of noise removal, ABF will outperform the bilateral filter and the OUM. ABF works well for both gray images and color images. Due to operation of sharpening of colour images along the edge slope tend to poseterize the image using ABF by pulling up or pulling down the colour images. The proposed method is effective at removing signal noise while enhancing the experimental results in perceptual quality both quantatively and qualitatively.

NEW APPROACH FOR STEGANOGRAPHY IN COLOR IMAGES WITH AN IMPROVED PSNR AND LSB TECHNIQUES

2012 ◽  
Vol 2 (5) ◽  
pp. 329-331
Author(s):  
G.S.Raman G.S.Raman ◽  
◽  
R.T.Subhalakshmi R.T.Subhalakshmi
Keyword(s):  
Color Images ◽  
New Approach

AN OPTIMAL REGION GROWING ALGORITHM FOR IMAGE SEGMENTATION

1987 ◽  
Vol 01 (03n04) ◽  
pp. 351-375 ◽  
Author(s):  
OLIVIER MONGA
Keyword(s):  
General Framework ◽  
Region Growing ◽  
Color Images ◽  
Natural Images ◽  
New Approach ◽  
Optimal Region ◽  
Efficient Data ◽  
Segmentation Problem ◽  
Merging Strategy

We present a new approach to the segmentation problem by optimizing a criterion which estimates the quality of a segmentation. We use a graph-based description of a partition of an image and a merging strategy based on the optimal use of a sequence of criteria. This method separates the strategy of making use of the segmentation criteria from their definition. An efficient data structure enables our implementation to have a low algorithmic complexity. Our method offers a general framework for solving a large class of segmentation problems. We show how to adapt this method to segment 2-D natural images including color images. This algorithm is also used for segmentation of 3-D images.

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