Image Coding Using Orthogonal Basis Functions
نویسنده
چکیده
The transform properties of several orthogonal basis functions are analysed in detail in this report, and their performance compared using a set of grayscale test images, containing both natural and artificial scenes. Well-defined image quality measures are used to determine the type of images that are most suitable for compression for a given basis function. The particular transforms that we have examined are the Discrete Cosine Transform, Discrete Tchebichef Transform, Walsh-Hadamard Transform and Haar Transforms. We have found that the Discrete Cosine Transform and Discrete Tchebichef Transform provide the greatest energy compactness for images containing natural scenes. For images with significant inter-pixel variations we have found that the Discrete Tchebichef Transform and Haar Transform provide the best performance. The Walsh-Hadamard Transform proved to be significantly less effective than either the Discrete Cosine or Discrete Tchebichef Transforms.
منابع مشابه
Codebook Generation for Vector Quantization on Orthogonal Polynomials based Transform Coding
In this paper, a new algorithm for generating codebook is proposed for vector quantization (VQ) in image coding. The significant features of the training image vectors are extracted by using the proposed Orthogonal Polynomials based transformation. We propose to generate the codebook by partitioning these feature vectors into a binary tree. Each feature vector at a non-terminal node of the bina...
متن کاملGeneralized Lapped Orthogonal Transform with Unequal-length Basis Functions
UNEQUAL-LENGTH BASIS FUNCTIONS Trac D. Tran Truong Q. Nguyen University of Wisconsin, ECE Department 1415 Engineering Dr., Madison WI 53706 [email protected], [email protected] ABSTRACT In this paper, the theory, design, and implementation of the Generalized Lapped Orthogonal Transform (GenLOT) with unequal-length basis functions are investigated. Necessary constraints on the building ...
متن کاملTuning Shape Parameter of Radial Basis Functions in Zooming Images using Genetic Algorithm
Image zooming is one of the current issues of image processing where maintaining the quality and structure of the zoomed image is important. To zoom an image, it is necessary that the extra pixels be placed in the data of the image. Adding the data to the image must be consistent with the texture in the image and not to create artificial blocks. In this study, the required pixels are estimated ...
متن کاملOrthogonal pyramid transforms for image coding
We describe a set of pyramid transforms that decompose an image into a set of basis functions that are (a) spatial-frequency tuned, (b) orientation tuned, (c) spatially localized, and (d) self-similar. For computational reasons the set is also (e) orthogonal and lends itself to (f) rapid computation. The systems are derived from concepts in matrix algebra, but are closely connected to decomposi...
متن کاملLinear phase paraunitary filter bank with filters of different lengths and its application in image compression
In this paper, the theory, structure, design, and implementation of a new class of linear-phase paraunitary filter banks (LPPUFB’s) are investigated. The novel filter banks with filters of different lengths can be viewed as the generalized lapped orthogonal transforms (GenLOT’s) with variable-length basis functions. Our main motivation is the application in blocktransform-based image coding. Be...
متن کاملThe Orientation Adaptive Lapped Orthogonal Transform for Image Coding
In this paper, a lapped orthogonal transform adapted for local directionality of an image is proposed and its application in adaptive image coding is presented. First, we address the problem to construct the lapped orthogonal transform with short and long functions such that the long functions are twice the length of the short functions, and derive the transform with the optimal short functions...
متن کامل