Complementary Color Wavelet: A Novel Tool for the Color Image/Video Analysis and Processing

In this paper we give a new method to find a grayscale image from a color image. The idea is that the structure tensors of the grayscale image and the color image should be as equal as possible. This is measured by the energy of the tensor differences. We deduce an Euler-Lagrange equation and a second variational inequality. The second variational inequality is remarkably simple in its form. Our equation does not involve several steps, such as finding a gradient first and then integrating it. We show that if a color image is at least two times continuous differentiable, the resulting grayscale image is not necessarily two times continuous differentiable.

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Using watermark visibility measurements to select an optimized pair of spot colors for use in a binary watermark

Electronic Imaging ◽

10.2352/issn.2470-1173.2020.15.color-195 ◽

2020 ◽

Vol 2020 (15) ◽

pp. 197-1-197-7

Author(s):

Alastair Reed ◽

Vlado Kitanovski ◽

Kristyn Falkenstern ◽

Marius Pedersen

Keyword(s):

Food Packaging ◽

Red Light ◽

Human Observer ◽

Viewing Distance ◽

Point Of Sale ◽

Complementary Color ◽

Low Visibility ◽

Packaging Industry ◽

Spot Color ◽

Selection Of

Spot colors are widely used in the food packaging industry. We wish to add a watermark signal within a spot color that is readable by a Point Of Sale (POS) barcode scanner which typically has red illumination. Some spot colors such as blue, black and green reflect very little red light and are difficult to modulate with a watermark at low visibility to a human observer. The visibility measurements that have been made with the Digimarc watermark enables the selection of a complementary color to the base color which can be detected by a POS barcode scanner but is imperceptible at normal viewing distance.

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Explanation of Color Lines Based on a Simple Color Image Model

Electronic Imaging ◽

10.2352/issn.2470-1173.2018.16.color-296 ◽

2018 ◽

Vol 2018 (16) ◽

pp. 296-1-296-5

Author(s):

Megan M. Fuller ◽

Jae S. Lim

Keyword(s):

Color Image ◽

Image Model

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Analysis of color Image Enhancement Using DWT, Wavelet Shrinkageand FHE Methods

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i8.21 ◽

2017 ◽

Vol 7 (8) ◽

pp. 56

Author(s):

Ashish Dwivedi ◽

Nirupma Tiwari

Keyword(s):

Image Enhancement ◽

Color Image ◽

Human Perception ◽

Histogram Equalization ◽

Wavelet Shrinkage ◽

Visual Appearance ◽

Enhancement Method ◽

Fuzzy Histogram ◽

Rgb Image

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.

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