Chitwong, Sakreya

Preferred name

Chitwong, Sakreya

Alternative Name

Chitwong, S.

Main Affiliation

School of Engineering

sakreya.ch@kmitl.ac.th

Now showing 1 - 10 of 20

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A fast intensity-hue-saturation fusion approach via principal component analysis for ikonos imagery
(2008-12-01)
Minhayenud, S.
;
Chitwong, S.
;
Cheevasuvit, F.
To enhance spatial information of low resolution multi-spectral (RGB) image, the intensity-hue-saturation (IHS) approach is perfectly used to fuse the low resolution RGB image and the high resolution panchromatic (Pan) image by replacing intensity component with the high-resolution Pan image. Disadvantage of the mentioned approach is that color of a fused image is changed because the saturation component is changed or spectral of the low resolution RGB image and the high resolution Pan image is different, that is, spectral information of the fused RGB image is distorted. This problem is important for applying the fused image for classification. To solve this problem, in this paper, we employ the principal component analysis (PCA) transformation to extract information from the low resolution RGB image. In procedure of fusion method, the first principal component is used to adjust brightness of the high resolution Pan image. The intensity component from IHS transformation is replaced by the adjusted brightness high-resolution Pan image. The experimental results by using IKONOS imagery show that the proposed approach is better performance than the original IHS methods by improving spectral distortion and still correlating to the Pan image.
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Speckle noise estimation with generalized gamma distribution
(2006-12-01)
Intajag, Sathit
;
Chitwong, Sakreya
Speckle noise is an inherent property of a synthetic aperture radar (SAR) image, and it generally tends to reduce the image resolution and contrast. The speckle noise estimation is an important prerequisite, whenever SAR image is used for object segmentation. Among the many methods in statistical description that have been proposed to perform the estimation, there exists a class of approaches that use a multiplicative model of speckled image formation, such as Rayleigh distribution, K-distribution, Weibull distribution etc. In this paper, generalized gamma (GG) distribution is used to estimate the noise characteristics. GG distribution is especially attractive because it contains several distributions as special cases, viz. Rayleigh, exponential, Weibull, and log-normal. The major parameter of the GG distribution is estimated according to maximum likelihood (ML) principle. The proposed method works successfully when the solution is located in the parameter space. For verifying the performance of the proposed scheme compared to the other methods, we use a χ<sup>2</sup> goodness-of-fit (GOF) test. © 2006 ICASE.
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Variable block size based adaptive watermarking in spatial domain
(2004-12-01)
Kimpan, Somchok
;
Lasakul, Attasit
;
Chitwong, Sakreya
In this paper, watermarking for still image is proposed. Image watermarking is performed in spatial domain that not only easy but also good result. A watermark image as binary image is embedded onto a original image by using method that gray levels of pixels in original image blocks is modified to appropriate an intensity of block. A variation of watermark image bits in order to embed the original image block selected affects to embedded block intensity and also it depends on original image block intensity. The block size is adapted as intensity of original image and capacity of watermark image in order to embed. As method of varying block size proposed, the effect of block size adaptation is good and also watermark image is robust to a number types of degradation. As the proposed method, quality of the original image is at least affected.
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Segmentation on edge preserving smoothing image based on graph theory
(2000-12-01)
Chitwong, S.
;
Cheevasuvit, F.
;
Dejhan, K.
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Mitatha, S.
;
Nokyoo, C.
The presented of noise in an image will cause many undesired small holes in the segmented image. This effect causes an important efficiency decreasing for classifying and describing objects. To remove the embed noise while the edges of the image still preserving, the edge preserving smoothing process must be applied. The smoothing process replaces the pixel intensity of the considered pixel by the average intensity of the most homogeneous mask among the proposed masks. The proposed masks can be preserved the thin region even its width is less than 3 pixels then, the smoothed image will be segmented by graph theory in order to obtain the higher accurate region's boundaries. In the mean time of segmentation process, the homogeneous threshold value has been applied to ensure that the maximum different gray value of each segmented region is controlled.
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Tracking notch filter for electrocardiograph measurement
(2006-01-01)
Witthayapradit, S.
;
Chitwong, S.
;
Tumthong, S.
This paper presents a tracking notch filter with opened-loop architecture for elimination of electric field frequency which can also interfere into ECG waveform. For measuring ECG waveform having the isolated instrumentation amplifier, at here, the quality factor (Q) of this filter is assigned about 8 and the attenuation of frequency noise is around of-35 dB and the gain of amplifier is of 1000. The frequency from frequency noise detector is multiplied by the frequency synthesizer. The clock signal from the frequency synthesizer is used for the switched capacitor network The performance of the proposed filter is tested with ECG waveform included frequency noise of 50Hz , 55Hz and 60Hz and also with measuring in Lead I of bipolar lead included noise signal of 50Hz for both cases, that is, before and after through the notch filter circuit in the time and frequency domain. The measured results have been successfully tested. In this paper, the discrete and passive devices are used for the designed circuit.
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Automatic SAR segmentation by fuzzy hit-or-miss and homogeneity index
(2005-12-01)
Intajag, Sathit
;
Tipsuwanporn, Vittaya
;
Chitwong, Sakreya
;
Suesut, Taweepon
;
Chevasuwit, Fusak
Object-based segmentation is the first essential step for image processing applications. Recently, segmentation techniques have been developed, but not enough to preserve the significant information contained in the small regions of an image. The proposed method is to partition an image into homogeneous regions by using a fuzzy hitor- miss operator with an inherent spatial transformation, which endows to preserve the small regions. In the proposed scheme, an iterative segmentation technique is formulated as consequential processes. Then, each time in iterating, hypothesis testing is used to evaluate the quality of the segmented regions with a homogeneity index. Our method is unsupervised and uses few parameters, most of which can be calculated from input data. This comparative study indicates that the new iterative segmentation algorithm provides acceptable results as seen in the tested examples of synthetic aperture radar (SAR) images. © 2005 by the American Society for Photogrammetry and Remote Sensing.
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Contrast enhancement of satellite image based on adaptive unsharp masking using wavelet transform
(2006-12-01)
Chitwong, S.
;
Phahonyothing, S.
;
Nilas, P.
;
Cheevasuvit, F.
This paper concerns with a method for unsharp masking for contrast enhancement of satellite image. We employ the nature of wavelet transform that separates the original image into low and high frequency sub-band images as low and high pass filter. Particularly, a number of high frequency sub-band images consist of horizontal, vertical, and diagonal coefficients that contain detail of information. Taking inverse wavelet transform of each sub-band image separately except low frequency one, we have each of high frequency information in horizontal, vertical, and diagonal image. All of them are scaled by the scaling factor in each one separately. Adaptive algorithm is implemented to results the suitable scaling factor to obtain the enhanced image corresponding with the given criterion based on variance of each area smooth and detail area. Experimental results show that our method performs well to high enhance in detail area and low in smooth area.
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SIL Verification of Safety Instrumented System for Block Valve System in Gas Pipeline by Using Markov Model Methodology
(2017-01-01)
Kongtong, P.
;
Chitwong, S.
This paper presents about methods for evaluation of safety integrity level (SIL) which is significant to reduce risk of failure of block valve in gas pipeline system by using Markov Model method which refer to International standard IEC 61508/61511. The reason of using Markov Model method is that it takes less time and more flexible than other methods to determine SIL. This method uses a qualitative approach showing Average Probability of Failure (PFDavg) rate data and repairing time from model to implement in further process.
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Local area histogram equalization based multispectral image enhancement from clustering using competitive hopfield neural network
(2003-10-01)
Chitwong, S.
;
Boonmee, T.
;
Cheevasuvit, F.
One of important issues for enhancing image based on local area histogram equalization (LHE) is a clustering or segmenting technique. That is, the more the accuracy of separating image into specified classes is needed, the better the performance of enhancement is. As mentioned objective, in this paper, the competitive Hopfield neural network (CHNN) is then proposed for clustering to the LHE based image enhancement. By using simulated image, standard image and mutispectral image from Landsat 7 satellite, experimental results are shown in both accuracy of clustering and variance of the enhanced image. The criteria for a good enhancement algorithm is that it can give high variance in detail area, low variance in smooth and edge areas. Also comparing the variance of the enhanced image by both LHE and global area histogram equalization (GHE) methods shows that one from LHE outperforms. In addition, the enlarged image from small area is shown clearly by visualization. All results compare with the conventional methods such as fuzzy c-means (FCM).
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Reference line extraction for automated data-entry system using wavelet transform
(2000-01-01)
Chitwong, Sakreya
;
Phonsri, Seksan
;
Thitimajshima, Punya
It is common that most document forms opt for the use of straight line as a reference position for filled information. The automated data-entry systems of such documents require an ability to search these reference lines so that the location of information in the forms can be known. This paper proposes a wavelet-based algorithm for extracting these reference lines in business forms. Stationary wavelet transform is used to transform a gray-level document image into different frequency-band images. The horizontal detail subband is then selected and passed through a post-processing to produce a binary bitmap of reference lines. The experimental results on synthetic and real document images will be given to illustrate the usefulness of such an algorithm.

Chitwong, Sakreya

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