Analysis of Landsat Images through Color Bands and Band Combinations using MATLAB
Maliha Tahir Butt, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Arbab Waseem Abbas, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Kanwal Lodhi, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Kashif Ali, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Mohib Ullah, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Corresponding Author:
Maliha Tahir Butt (malihabutt7@gmail.com)
Abstract:
Image processing is a procedure to execute operations on an image, in order to get an enhanced image or to takeout some information from it. It is a type of signal processing in which input is an image and output may be image or features associated with that image. These sensors measure the radiation in different wavelengths or bands, which are then processed to create images that can be used for analysis and interpretation. This paper discusses the key of color bands and band combinations in image processing, providing examples of how these techniques can be used to extract information that is not visible in individual bands. The paper also examines some of the challenges associated with using color bands and band combinations and explores potential future developments in this area. In this paper the combinations of RGB color bands used to identify differentiation. This research also applied different features of image on a single image. In single image Swapping, enhancement, hue, saturation, Edge Detection, Value techniques are applied. Matlab's color picture feature is important because it enables the encoding and manipulation of images with multiple color channels, which offers greater detail and visual fidelity than grayscale images.
Keywords:
Band; Sensors; Remote; Color Band; Band Combination