Jonas Valantinas

The use of image smoothness estimates in speeding up fractal image compression

The paper presents a new attempt to speed up fractal image encoding. The range blocks and corresponding domain blocks are categorized depending on their smoothness parameter values (smoothness estimates), introduced, from the first, to characterize manifestation of high frequency components in the image. The searching of the best matched domain block is carried out between the neighbouring (or, within the same) smoothness classes. The computational complexity of the fractal image encoding process is reduced considerably. Theoretical and experimental investigations show that extremely high compression time savings are achieved for images of size 512x512.

Accelerating compression times in block based fractal image coding procedures

Fractal image compression turns out to be a powerful and competitive technology, which can be successively applied to a still image coding, especially at high compression rates. Unfortunately, a large amount of computation needed for the compression stage remains to be a serious obstacle in exploring this new perspective approach. Diversified attempts are made to improve the situation. In particular, theoretical investigations and experiments show that the problem-oriented use of invariant image parameters (image smoothness estimates) can serve the purpose.

SPEEDING-UP IMAGE ENCODING TIMES IN THE SPIHT ALGORITHM

In this paper, a new approach (scheme) to the analysis of quad-trees in the discrete wavelet spectrum of a digital image is proposed. During the pre-scanning phase, the proposed scheme generates problem-oriented binary codes for the whole set of quad-tree roots (wavelet coefficients) and thereby accumulates information on the signi-ficance of respective descendants (wavelet coefficients comprising quad-trees on the view). The developed scheme can be efficiently applied to any zero-tree based image coder, such as the embedded zero-tree wavelet (EZW) algorithm of Shapiro and set partitioning in hierarchical trees (SPIHT) by Said and Pearlman. Fairly impressive performance of the proposed quad-tree analysis scheme, in the sense of image encoding times, is demonstrated using the SPIHT algorithm and the discrete Le Gall wavelet transform. http://dx.doi.org/10.5755/j01.itc.40.1.187

A New Le Gall Wavelet-Based Approach to Progressive Encoding and Transmission of Image Blocks

In this paper, a modified version of the discrete reversible (integer-to-integer) Le Gall wavelet transform (DLGT), distinguishing itself by apparently improved space localization properties and visibly extended potential capabilities, is proposed. The key point of the proposal – ensuring full decorrelation of Le Gall wavelet coefficients across the lower scales. Based on the latter circumstance, a novel exceptionally fast procedure for computing the integer DLGT spectra of the selected image blocks (regions of interest - ROI) is presented. It is shown that the new developments can be efficiently applied to progressive encoding and transmission of image blocks. Progressive encoding and transmission of image blocks is achieved by first transmitting a “rough” estimate of the original image, then sending further details related to one or another image block (ROI). To translate the idea into action, the zero-tree-based encoder SPIHT with an improved quad-tree analysis scheme is employed. DOI: http://dx.doi.org/10.5755/j01.itc.41.3.920

Improving compression time in zero-tree based image coding procedures

In this paper, a novel scheme for the accelerated analysis of quad-trees in the discrete wavelet spectrum of a digital image is proposed. During the pre-scanning step, the proposed scheme generates objective and specially structured binary codes for the whole set of quad-tree roots (wavelet coefficients) and thereby accumulates facts on the significance of respective descendants (wavelet coefficients comprising quad-trees on the view). The developed scheme can be successfully applied to any zero-tree based image coding procedure, such as the embedded zero-tree wavelet (EZW) algorithm of Shapiro and set partitioning in hierarchical trees (SPIHT) by Said and Pearlman. Exceptionally high performance of the proposed quad-tree analysis scheme, in the sense of image encoding times, is demonstrated using the EZW algorithm and the discrete Le Gall wavelet transform.

Improving Space Localization Properties of the Discrete Wavelet Transform

Abstract. In this paper, a modified version of the discrete wavelet transform (DWT), distinguishing itself with visibly improved space localization properties and noticeably extended potential capabilities, is proposed. The key point of this proposal is the full decorrelation of wavelet coefficients across the lower scales. This proposal can be applied to any DWT of higher orders (Le Gall, Daubechies D4, CDF 9/7, etc.). To open up new areas of practical applicability of the modified DWT, a novel exceptionally fast algorithm for computing the DWT spectra of the selected signal (image) blocks is presented. In parallel, some considerations and experimental results concerning the energy compaction property of the modified DWT are discussed.

On the use of Le Gall wavelets in implementing locally progressive digital signal coding idea

The main goal of progressive encoding and transmission of digital signals is to allow the user to identify relevant features in a signal as quickly as possible at minimum cost. Locally progressive encoding and transmission can be achieved by first transmitting a low resolution approximation (ldquoroughrdquo estimate) of the original signal, then sending further details related to one or another selected (mostly, at the users request) block of the signal. In this paper, we propose a novel wavelet-based approach to implementing of a locally progressive digital signal coding idea. The proposed approach explores both the newly developed fast procedures for the evaluation of the discrete wavelet transform for signal blocks and some efficient wavelet-based signal encoders.

On the Use of Discrete Wavelets in Implementing Defect Detection System for

In this paper, a novel wavelet-based approach to the detection of defects in grey-level texture images is proposed. This new approach (system) explores specific properties of the discrete wavelet transform (DWT), evaluates the statistical analysis results associated with well-defined and task-oriented subsets of DWT spectral coefficients, and generates defect detection criteria which, in their turn, evaluate many-sided nature of potential defects in texture images and leave space for controlling the risk, i.e. for controlling the percentage of false positives and/or false negatives in a particular class of texture images. The experimental results demonstrating the use of the proposed system for the visual inspection of ceramic tiles, obtained from the real factory environment, and textile fabric scraps are also presented. DOI: http://dx.doi.org/10.5755/j01.itc.45.2.12654

Wavelet-based Defect Detection System for Grey-level Texture Images

In this study, a new wavelet-based approach (system) to the detection of defects in grey-level texture images is presented. This new approach explores space localization properties of the discrete wavelet transform (DWT) and generates statistically-based parameterized defect detection criteria. The introduced system’s parameter provides the user with a possibility to control the percentage of both the actually defect-free images detected as defective and/or the actually defective images detected as defect-free, in the class of texture images under investigation. The developed defect detection system was implemented using discrete Haar and Le Gall wavelet transforms. For the experimental part, samples of ceramic tiles, as well as glass samples, taken from real factory environment, were used.

Haar Wavelet-Based Approach to Locating Defects in Texture Images

In this paper, a novel Haar wavelet-based approach to extracting and locating surface defects in grey-level texture images is proposed. This new approach explores space localization properties of the discrete Haar wavelet transform (HT), performs task-oriented statistical analysis of well-defined non-intersecting subsets of HT spectral coefficients, and generates parameterized defect detection criteria with an installed additional capability to locate surface defects in defective texture images. The preliminary experimental analysis results demonstrating the use of the developed approach to the automated visual inspection of ceramic tiles, obtained from the real factory environment, are also presented.