Ferda Ernawan

A generic psychovisual error threshold for the quantization table generation on JPEG image compression

The quantization process is a main part of image compression to control visual quality and the bit rate of the image output. The JPEG quantization tables are obtained from a series of psychovisual experiments to determine a visual threshold. The visual threshold is useful in handling the intensity level of the colour image that can be perceived visually by the human visual system. This paper will investigate a psychovisual error threshold at DCT frequency on the grayscale image. The DCT coefficients are incremented one by one for each frequency order. Whereby, the contribution of DCT coefficients to the error reconstruction will be a primitive pyschovisual error. At certain threshold being set on this psychovisual error, the new quantization table can be generated. The experimental results show that the new quantization table from psychovisual error threshold for DCT basis functions gives better quality image at lower average bit length of Huffman code than standard JPEG image compression.

An efficient 2×2 Tchebichef moments for mobile image compression

Currently mobile digital image applications transmit a lot of images back and forth. Image compression is needed to reduce transmission payload at the expense of lower quality. At the same time, mobile devices are only expected to be equipped with lower computing power and storage. They need an efficient compression scheme especially for small images. The standard JPEG using discrete Cosine transform is a popular lossy image compression. Alternatively, this paper introduces 2×2 Tchebichef moments transform for the efficient image compression. In the previous research, larger sub-block discrete Tchebichef moments have been used extensively for image compression. The comparisons between JPEG compression and 2×2 Tchebichef moments image compressions shall be done. The preliminary experiment results show that 2×2 Tchebichef moments transform has the potential to easily perform better than JPEG image compression. The 2×2 Tchebichef moments provides an efficient and compact support for image compression.

ADAPTIVE TCHEBICHEF MOMENT TRANSFORM IMAGE COMPRESSION USING PSYCHOVISUAL MODEL

An extension of the standard JPEG image compression known as JPEG-3 allows rescaling of the quantization matrix to achieve a certain image outp ut quality. Recently, Tchebichef Moment Transform (TMT) has been introduced in the field of image compression. TMT has been shown to perform better than the standard JPEG image compression. This study presents an adaptive TMT image compression. This task is obtained by generating custom quantization tables f or low, medium and high image output quality levels based on a psychovisual model. A psychovisual model is developed to approximate visual threshold on Tchebichef moment from image reconstruction error. The contribution of each moment will be investigated and analy zed in a quantitative experiment. The sensitivity of TM T basis functions can be measured by evaluating the ir contributions to image reconstruction for each mome nt order. The psychovisual threshold model allows a developer to design several custom TMT quantization tables for a user to choose from according to his or her target output preference. Consequently, these quant ization tables produce lower average bit length of Huffman code while still retaining higher image quality tha n the extended JPEG scaling scheme.

Image watermarking using psychovisual threshold over the edge

Currently the digital multimedia data can easily be copied. Digital image watermarking is an alternative approach to authentication and copyright protection of digital image content. An alternative embedding watermark based on human eye properties can be used to effectively hide the watermark image. This paper introduces the embedding watermark scheme along the edge based on the concept of psychovisual threshold. This paper will investigate the sensitivity of minor changes in DCT coefficients against JPEG quantization tables. Based on the concept of psychovisual threshold, there are still deep holes in JPEG quantization values to embed a watermark. This paper locates and utilizes them to embed a watermark. The proposed scheme has been tested against various non-malicious attacks. The experiment results show the watermark is robust against JPEG image compression, noise attacks and low pass filtering.

Tchebichef moment transform on image dithering for mobile applications

Currently, mobile image applications spend a lot of computing process to display images. A true color raw image contains billions of colors and it consumes high computational power in most mobile image applications. At the same time, mobile devices are only expected to be equipped with lower computing process and minimum storage space. Image dithering is a popular technique to reduce the numbers of bit per pixel at the expense of lower quality image displays. This paper proposes a novel approach on image dithering using 2x2 Tchebichef moment transform (TMT). TMT integrates a simple mathematical framework technique using matrices. TMT coefficients consist of real rational numbers. An image dithering based on TMT has the potential to provide better efficiency and simplicity. The preliminary experiment shows a promising result in term of error reconstructions and image visual textures.

Spectrum Analysis of Speech Recognition via Discrete Tchebichef Transform

Speech recognition is still a growing field. It carries strong potential in the near future as computing power grows. Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) is the traditional technique to analyze frequency spectrum of the signal in speech recognition. Speech recognition operation requires heavy computation due to large samples per window. In addition, FFT consists of complex field computing. This paper proposes an approach based on discrete orthonormal Tchebichef polynomials to analyze a vowel and a consonant in spectral frequency for speech recognition. The Discrete Tchebichef Transform (DTT) is used instead of popular FFT. The preliminary experimental results show that DTT has the potential to be a simpler and faster transformation for speech recognition.

Psychovisual model on discrete orthonormal transform

Discrete Orthonormal Transform has been a basis for digital image processing. The lesser coefficients of a Discrete Orthonormal Transform to reconstruct an image is the more compact support the Discrete Orthonormal Transform provides to an image. Tchebychev Moment Transform has been shown to provide a more compact support to an image than the popular Discrete Cosine Transform. This paper will investigate the contribution of each coefficient of the Discrete Orthonormal Transform to the image reconstruction. The error threshold in image reconstruction will be the primitive of Psychovisual Model to an image. An experimental result shall show that the Psychovisual Model will provide a statistically efficient error threshold for image reconstruction.

Efficient Discrete Tchebichef on SpectrumAnalysis of Speech Recognition

Speech recognition is still a growing field of importance. The growth in computing power will open its strong potentials for full use in the near future. Spectrum analysis is an elementary operation in speech recognition. Fast Fourier Transform (FFT) has been a traditional technique to analyze frequency spectrum of the signals in speech recognition. FFT is computationally complex especially with imaginary numbers. The Discrete Tchebichef Transform (DTT) is proposed instead of the popular FFT. DTT has lower computational complexity and it does not require complex transform dealing with imaginary numbers. This paper proposes a novel approach based on 256 discrete orthonormal Tchebichef polynomials as efficient technique to analyze a vowel and a consonant in spectral frequency of speech recognition. The comparison between 1024 discrete orthonormal Tchebichef transform and 256 discrete orthonormal Tchebichef transform has been done. The preliminary experimental results show that 256 DTT has the potential to be more efficient to transform time domain into frequency domain for speech recognition. 256 DTT produces simpler output than 1024 DTT in frequency spectrum. At the same time, 256 Discrete Tchebichef Transform can produce concurrently four formants F1, F2, F3 and F4.

A Psychovisual Threshold for Generating Quantization Process in Tchebichef Moment Image Compression

A human visual system can hardly respond to small differences in image signals. A full colour image carries a certain amount of perceptual redundancy for the human eyes. The sensitivity human eye of the color image can be measured by a psychovisual threshold. The sensitivity of the human eye is useful for perceptual visual image in image compression. The quantization tables are obtained to determine psychovisual threshold that can be perceived visually significant by the human eye. This paper introduces the concept of psychovisual threshold into Tchebichef moment image compression. This paper will investigate the contribution of each moment coefficient to the image reconstruction. The error threshold from the contribution of its moments in image reconstruction will be the primitive of psychovisual threshold to an image. This paper presents a new technique to generate quantization table for an optimal TMT image compression based on psychovisual error threshold. The experimental results show that these new finer quantization tables provide a statistically better image quality output at lower average bit length of Huffmans code than previously proposed TMT quantization.

Tchebichef Moment Transform for colour image dithering

Currently, small mobile devices may not have the capability to display high fidelity true colour images. It is expected to have limited capability in computational power and storage. However, a small mobile device is expected to perform efficiently in displaying images. A dithering technique is called for here in order to improve the perceptual visual quality of the limited bit depth images. Typically, a true colour image is reduced down to fewer bits per pixel. In order to efficiently dither a colour image on small mobile devices, this paper proposes 2×2 Tchebichef Moment Transform (TMT) approach. Earlier, a 2×2 Discrete Wavelet Transform (DWT) has been proposed for better image quality on dithering. The 2×2 TMT has been chosen since it performs better than the 2×2 DWT. TMT incorporates simplified mathematical framework technique using matrices. The result shows that 2×2 TMT gives perceptually better quality on colour image dithering in significantly efficient fashion.