Designing A New Low Complexity Approximation For Image Compression

3363 Words14 Pages
ABSTRACT
We focus on approximate algorithms for the computation of the 8-point DCT. While not computing the DCT exactly, approximate methods can provide meaningful estimations at low-complexity requirements. Prominent techniques include the signed discrete cosine transform (SDCT), the Bouguezel–Ahmad–Swamy (BAS) series of algorithms, and the level-1 approximation by Lengwehasatit-Orteg. All above mentioned techniques possess extremely low arithmetic complexities. These techniques have some defaults, So proposed technique is to overcome all the defaults and performed well compare to above techniques. The aim of this correspondence is to introduce a new low-complexity DCT approximation for image compression in conjunction with a
…show more content…
A digital image is composed of a finite number of elements, each of which has a particular location and value. These elements are referred to as picture elements, image

Bhargava R Mamidi
(012607138)
California State University
Long beach, California, United States
Bhargavareddy450@gmail.com

elements and pixels. Pixel is most widely used to denote the elements of a digital image.
Images play the single most important role in human perception. Humans are limited to the visual band of the electromagnetic spectrum, imaging machines cover almost the entire electromagnetic spectrum, ranging from gamma to radio waves. They can operate on images generated by sources that humans are not accustomed to associating with images. These include ultrasound, electron microscopy, and computer-generated images. Thus, digital image processing encompasses a wide and varied field of applications.
Digital image processing is the use of computer algorithms to perform image processing on digital images. Digital image processing has the same advantages over analog image processing as digital signal processing has over analog signal processing it allows a much wider range of algorithms to be applied to the input data, and can avoid problems such as the build-up of noise and signal distortion during processing. Image processing is a subclass of signal processing concerned specifically with
Open Document