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 15

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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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Speckle noise reduction using adaptive singular value decomposition in logarithmic domain
(2005-12-01)
Chitwong, S.
;
Thongsila, A.
;
Intajag, S.
;
Nilas, P.
;
Cheevasuvit, F.
This paper presents applying the singular value decomposition to reduce speckle noise. Generally, it is used to filter the additive Gaussian noise with zero mean and any variance. Since speckle noise is in multiplicative model, to transform multiplicative model into additive model, we then employ logarithmic transformation. In this paper, speckle noise is generally modeled as Gamma distribution function corresponding with speckle noise of synthetic aperture radar (SAR) imagery applied. All singular value decomposition based filtering processing is in logarithmic domain. Threshold value to determine the effective rank and orders of matrix are adapted as homogeneity analysis. The orders of matrix are consisted of 16 by 16, 8 by 8 and 4 by 4. Normally, the results of the singular value decomposition based filtering after that the filtered matrix is transformed into spatial domain by exponential function is in block-fashion, then blocking effect is occurred. To smooth, the filtered matrix is performed as average filtering by using a number of pixels of 4 by 4 pixels around center of one. Experiments are tested using both simulated image and real image. Signal to noise ratio and equivalent number of looks are employed to evaluate the performance of our method. Our results are good enough when compared with the recent results at which such method is more complex. © 2005 by the American Society for Photogrammetry and Remote Sensing.
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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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Enhancement of color image obtained from PCA-FCM technique using local area histogram equalization
(2002-12-01)
Chitwong, S.
;
Boonmee, T.
;
Cheevasuvit, F.
This paper presents local area enhancement of the segmented color image obtained from the multi-spectral image clustering by using FCM (fuzzy c-means). In case, the multi-spectral images, which have the number of bands more than that of 3, must decrease the data volume to remain the number of bands of 3 in order to correspond with the meaning of red, green, and blue images. PCA (Principal Components Analysis) is then used to transform original multi-spectral images into PCA images. The first three components having information more than that of original images of 95% is assigned as red, green, and blue images, namely RGB color image. FCM clustering apply to RGB color image, separately. This method is called the PCA-FCM technique being the multi-spectral image clustering. By applying such technique, the result images consisted of red, green, and blue images separately are the segmented images. By histogram equalization algorithm, the result of local area enhancement based on a number of clusters as the segmented image can solve effect of intensity saturation from global area enhancement and the perceptibility of color image is clearly improved.
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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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Fusion of principal component of multispectral bands with PAN band using HIS and wavelet transform
(2002-01-01)
Chitwong, S.
;
Cheevasuvit, F.
;
Homthong, J.
Since RGB images derived from multispectral (TM) images will lose some information, in this paper we present the method to solve such problem by using principal component analysis (PCA) which transforms TM images into the principal component images (PCs), while the high resolution PAN data is decomposed by wavelet transform. Thus, RGB images are assigned by the first three principal component images which normally have approximately 95% of the information in the original images. The intensity image from RGB to HIS transformation is replaced by the lower frequency coefficient of wavelet transform of PAN data corresponding to multispectral images. HIS to RGB transformation is then applied. The fused RGB image using our method can obtain more details.

Chitwong, Sakreya

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