Colour Image Represention of Multispectral Image Fusion

Abstract

The availability of imaging sensors operating in multiple spectral bands has led to the requirement of image fusion algorithms that would combine the image from these sensors in an efficient way to give an image that is more perceptible to human eye. Multispectral Image fusion is the process of combining images optically acquired in more than one spectral band. In this paper, we present a pixel-level image fusion that combines four images from four different spectral bands namely near infrared(0.76-0.90um), mid infrared(1.55-1.75um),thermal-infrared(10.4-12.5um) and mid infrared(2.08-2.35um) to give a composite colour image. The work coalesces a fusion technique that involves linear transformation based on Cholesky decomposition of the covariance matrix of source data that converts multispectral source images which are in grayscale into colour image. This work is composed of different segments that includes estimation of covariance matrix of images, cholesky decomposition and transformation ones. Finally, the fused colour image is compared with the fused image obtained by PCA transformation.

Human visualization system based intensive contrast improvement of the collected COVID-19 images

“…The images are color with 24-bit depth as 3 dimension or channels and joint photographic experts group (JPEG) format with different size of pixel for each image. In pre-processing stage each image has converted from red, green, and blue (RGB) to Gray, each color can only have values 0 to 255 for 8-bit [19]. In (1) has been used for converting purposes from a color image to grayscale.…”