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Recently, wavelet transform has proven to be very effective in medical image compression. However, the choice of wavelet filters is a vital factor that can be determined the compression performance. The aim of this paper is to investigate the effect of applying different types of wavelet filters belonging to orthogonal and biorthogonal wavelets with different orders on the panoramic dental x-ray images...
In this paper, we propose a multi-focus image fusion approach based on Stationary Wavelet Transform (SWT) and extended the Spatial Frequency Measurements (SFM). Our proposed approach, two fused images are firstly decomposed into four subbands, which are one approximation subband (LL) and three details subbands (HL, LH and HH). Next, each subband is partitioned into blocks and each block is identified...
Assessment of the compressed image quality is an important issue for image processing system. In this paper, we propose a novel objective assessment to measure the quality of gray scale compressed image, which is developed from the fundamental objective measurement. It is also correlated well with human response and least time taken comparable to some existing measurements. The proposed measurement,...
Measurement of the quality of distorted image still remains an important issue. In this paper, we propose a new objective measurement, denoted as image quality score (IQS) that better matches the visual information fidelity (VIF) than using fundamental image quality measurements. IQS can be used to measure the quality of gray scale image in different distortion types such as blurring, additive Gaussian...
Texture has been widely accepted as a feature of primary significance in digital image processing field. In this paper, we present a simple approach to classify types of rock into three groups, which are homogenous, non-homogenous dark rock or bright rock containing less finer black grains, and non-homogenous bright rocks which contain numerous finer black grains or large black grains. Modified Spatial...
Noise suppression is one of the most essential processes for image processing. The goal of the noise suppression is how to remove the noise while keeping the important image features as much as possible. In this paper, we present an adaptive block-based singular value decomposition method for noise suppression. Instead of applying block-based singular value decomposition (BSVD) directly to noisy images,...
This paper presents the Thai syllable segmentation of human speech algorithm using the 1-D stationary wavelet transform (SWT). The detail coefficient component of SWT, which represents the high frequency part of input signal, is used to analyze the boundaries of syllables. Our proposed approach, the input signals are separated into two parts. First part, the data of signal is used to find the boundaries...
Noise reduction is one of the most important processes to enhance the quality of reconstructed image. In this paper, we present an adaptive block-based singular value decomposition method for noise reduction. Instead of applying block-based singular value decomposition (BSVD) directly to noisy images, we propose to apply BSVD on the noisy edge image version obtained from the difference between the...
Evaluation of the quality of image compression still remains an important issue. In this paper, we propose a novel objective assessment to evaluate the quality of gray scale compressed images. An image characteristic measurement, Spatial Frequency Measurement (SFM), is employed to get the new objective measurements, which are Mean Square Error with SFM (MSESFM), Edge Measurement with SFM (ESFM) and...
Evaluation of the quality of image compression still remains an important issue. In this work, we propose the new objective measurements, which are developed from five traditionally simple measurements (Mean Square Error, Edge Measurement, Correlation Measurement, Visual Human System and Spectral Measurement). In our study, we evaluated the quality of the compressed gray-scale images using both objective...
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