Current methods for image segmentation are confused by artifacts such as highlights, because they are not based on any physical model of these phenomena. In this paper, we present an approach to color image understanding that accounts for color variations due to highlights and shading. Based on the physics of reflection by dielectric materials, such as plastic, we show that the color of every p...

The Principal Component Analysis Network (PCANet), which is one of the recently proposed deep learning architectures, achieves the state-of-the-art classification accuracy in various databases. However, the performance of PCANet may be degraded when dealing with color images. In this paper, a Quaternion Principal Component Analysis Network (QPCANet), which is an extension of PCANet, is proposed...

The color reproduction of an image sensor is one of the important characteristics which determine the performance of the image sensor. Recently, the pixel size of image sensor has become smaller due to the demand of large pixel count. So, small F-number lens is needed to improve the sensitivity. However, the crosstalk component of spectral sensitivity characteristics increases due to using the ...

This paper proposes a method to apply BPCSSteganography that we have already proposed for gray scale images to palette-based images which consists of a palette storing color vector information and an index image whose pixel value is corresponding to a index in the palette. A palette-based images can be represented by combining R G and B color component images. We embed secret information into t...

Hyperspectral images, contain data from a large number of contiguous bands and, therefore, cannot be displayed directly using a color display system. In this paper, an independent component analysis-based (ICA-based) approach for the problem of fusing hyperspectral images to three-band images for color display purposes is proposed. Correlation coefficient and mutual information (ICA-CCMI) are u...

In this paper, a denoising approach, which exploits patchredundancy for removing Gaussian noise from RGB color images is described. Both geometrical and photometrical similarity of image patches have to be considered for learning the parameters of this Patch-based Locally Optimal Weiner(PLOW) filer. K-means clustering,with LARK(Locally Adaptive Regression Kernel) features, is used to identify t...