• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.21-29
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• 2019

This paper proposes a novel framework for image fusion of satellite imagery to enhance spatial resolution of the image via structure-texture decomposition. The resolution of the satellite imagery depends on the sensors, for example, panchromatic images have high spatial resolution but only a single gray band whereas multi-spectral images have low spatial resolution but multiple bands. To enhance the spatial resolution of low-resolution images, such as multi-spectral or infrared images, the proposed framework combines the structures from the low-resolution image and the textures from the high-resolution image. To improve the spatial quality of structural edges, the structure image from the low-resolution image is guided filtered with the structure image from the high-resolution image as the guidance image. The combination step is performed by pixel-wise addition of the filtered structure image and the texture image. Quantitative and qualitative evaluation demonstrate the proposed method preserves spectral and spatial fidelity of input images.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1296-1305
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• 2019

To solve the problem of poor noise suppression capability and frequent loss of edge contour and detailed information in current fusion methods, an infrared and visible light image fusion method based on variational multiscale decomposition is proposed. Firstly, the fused images are separately processed through variational multiscale decomposition to obtain texture components and structural components. The method of guided filter is used to carry out the fusion of the texture components of the fused image. In the structural component fusion, a method is proposed to measure the fused weights with phase consistency, sharpness, and brightness comprehensive information. Finally, the texture components of the two images are fused. The structure components are added to obtain the final fused image. The experimental results show that the proposed method displays very good noise robustness, and it also helps realize better fusion quality.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1517-1522
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• 2017

Among single image SR techniques, the TV based SR approach seems most successful in terms of edge preservation and no artifacts. But, this approach achieves insufficient SR for texture component. In this paper, we proposed a new TV-G decomposition based SR method to solve this problem. We proposed the SVR based up-sampling to get better edge preservation in the structure component. The NNE used the relaxed constraint to improve the NE. We used the NNE based learning method to improve the resolution of the texture component. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed SR method when comparing with conventional interpolation method, ScSR, TV and NNE.

• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.6
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• pp.1077-1085
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• 1997

This study was carried out to elucidate the utilization of the fusant for shortening the ripening time by making an observation of the microstructure and the profile of component change. In ripening cheese, moisture content of the sample treated with tested strain is not a remarkable difference among the test samples. With an increase of the ripening time, L. helveticus showed the highest increase in protein content, followed by fusant, and then L. bulgaricus. The fat content of all starters was gradually decreased while it was it was rapidly decreased after 7 days. The pH of all starters was gradually decreased when the ripening time increased. The titratable acidity was greatly increased between a 9th day and a 15th day ripening. In investigating the light microscopic microstructure of ripened cheese samples, the sample treated with fusant indicated little difference from the other starters in decomposition of protein and fat components by microbial enzymes. In SEM observation, the structure of all cheese samples was uniform and the rough texture was converted into smooth texture by the interaction of cheese components and the abscission of single bond in casein matrix when the ripening time is increased. The fusant showed similar results in the examination of component change and its microstructure compared with the other starters. Therefore, it was revealed that the fusant can be partially used as a cheese starter instead of conventional starters by replacing them or combining them together with the other starters for shortening the ripening time.

• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.521-532
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• 2015

This paper presents a piecewise image denoising with multi-scale block region detector based on quadtree structure for effective image restoration. Proposed piecewise image denoising method suggests multi-scale block region detector (MBRD) by dividing whole pixels of a noisy image into three parts, with regional characteristics: strong variation region, weak variation region, and flat region. These regions are classified according to total pixels variation between multi-scale blocks and are applied principal component analysis with local pixel grouping, bilateral filtering, and structure-preserving image decomposition operator called relative total variation. The performance of proposed method is evaluated by Experimental results. we can observe that region detection results generated by the detector seems to be well classified along the characteristics of regions. In addition, the piecewise image denoising provides the positive gain with regard to PSNR performance. In the visual evaluation, details and edges are preserved efficiently over the each region; therefore, the proposed method effectively reduces the noise and it proves that it improves the performance of denoising by the restoration process according to the region characteristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.412-434
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• 2023

This study discusses the high-order diffusion method in the wavelet domain. It aims to improve the edge protection capability of the high-order diffusion method using wavelet coefficients that can reflect image information. During the first step of the proposed diffusion method, the wavelet packet decomposition is a more refined decomposition method that can extract the texture and structure information of the image at different resolution levels. The high-frequency wavelet coefficients are then used to construct the edge detection function. Subsequently, because accurate wavelet coefficients can more accurately reflect the edges and details of the image information, by introducing the idea of state weight, a scheme for recovering wavelet coefficients is proposed. Finally, the edge detection function is constructed by the module of the wavelet coefficients to guide high-order diffusion, the denoised image is obtained. The experimental results showed that the method presented in this study improves the denoising ability of the high-order diffusion model, and the edge protection index (SSIM) outperforms the main methods, including the block matching and 3D collaborative filtering (BM3D) and the deep learning-based image processing methods. For images with rich textural details, the present method improves the clarity of the obtained images and the completeness of the edges, demonstrating its advantages in denoising and edge protection.

• Analytical Science and Technology
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• v.19 no.5
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• pp.376-382
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• 2006

In this work, pitch/activated carbon/$TiO_2$ composite were prepared by $CCl_4$ solvent method with different mixing ratios. The BET surface area of pitch/activated carbon/$TiO_2$ composite has a significantly increase with increasing activated carbon content in pitch/activated carbon/$TiO_2$ composite. The surface structure and elemental compositions of the composite were studied by SEM and EDX, respectively. The SEM results were presented to the characterization of porous texture on the pitch/activated carbon/$TiO_2$ composite. And EDX data was shown the presence of C, O, S, Ti and other elements. The structural properties of the composite were studied in XRD measurements. The $TiO_2$ crystal phases of the pitch/activated carbon/$TiO_2$ composite had lots of rutile-type structure which transforms from anatase-type with a little of anatase-type structure. The photocatalytic activities of the composite were evaluated using a photo-decomposition method under UV lamp. The pitch/activated carbon/$TiO_2$ composites were observed better photocatalytic activity than that of pristine $TiO_2$.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.371-384
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• 2019

Motion perception has been tremendously improved in neuroscience and computer vision. The baseline motion perception model is mediated by the dorsal visual pathway involving the cortex areas the primary visual cortex (V1) and the middle temporal (V5 or MT) visual area. However, few works have been done on the extension of neural models to improve the efficacy and robustness of motion perception of real sequences. To overcome shortcomings in situations, such as varying illumination and large displacement, an adaptive V1-MT motion perception (Ad-V1MTMP) algorithm enriched to deal with real sequences is proposed and analyzed. First, the total variation semi-norm model based on Gabor functions (TV-Gabor) for structure-texture decomposition is performed to manage the illumination and color changes. And then, we study the impact of image local context, which is processed in extra-striate visual areas II (V2), on spatial motion integration by MT neurons, and propose a V1-V2 method to extract the image contrast information at a given location. Furthermore, we take feedback inputs from V2 into account during the polling stage. To use the algorithm on natural scenes, finally, multi-scale approach has been used to handle the frequency range, and adaptive pyramidal decomposition and decomposed spatio-temporal filters have been used to diminish computational cost. Theoretical analysis and experimental results suggest the new Ad-V1MTMP algorithm which mimics human primary motion pathway has universal, effective and robust performance.

• Journal of the Optical Society of Korea
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• v.20 no.6
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• pp.745-751
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• 2016

A detection algorithm, based on the combined local-global (CLG) optical-flow model and Gaussian pyramid for a moving target appearing against a dynamic background, can compensate for the inadaptability of the classic Horn-Schunck algorithm to illumination changes and reduce the number of needed calculations. Incorporating the hypothesis of gradient conservation into the traditional CLG optical-flow model and combining structure and texture decomposition enable this algorithm to minimize the impact of illumination changes on optical-flow estimates. Further, calculating optical-flow with the Gaussian pyramid by layers and computing optical-flow at other points using an optical-flow iterative with higher gray-level points together reduce the number of calculations required to improve detection efficiency. Finally, this proposed method achieves the detection of a moving target against a dynamic background, according to the background motion vector determined by the displacement and magnitude of the optical-flow. Simulation results indicate that this algorithm, in comparison to the traditional Horn-Schunck optical-flow algorithm, accurately detects a moving target undergoing illumination changes against a dynamic background and simultaneously demonstrates a significant reduction in the number of computations needed to improve detection efficiency.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.579-588
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• 2013

This paper proposes an effective watermarking approach for copyright protection of fire video images. The proposed watermarking approach efficiently utilizes the inherent characteristics of fire data with respect to color and texture by using a gray level co-occurrence matrix (GLCM) and fuzzy c-means (FCM) clustering. GLCM is used to generate a texture feature dataset by computing energy and homogeneity properties for each candidate fire image block. FCM is used to segment color of the fire image and to select fire texture blocks for embedding watermarks. Each selected block is then decomposed into a one-level wavelet structure with four subbands [LL, LH, HL, HH] using a discrete wavelet transform (DWT), and LH subband coefficients with a gain factor are selected for embedding watermark, where the visibility of the image does not affect. Experimental results show that the proposed watermarking approach achieves about 48 dB of high peak-signal-to-noise ratio (PSNR) and 1.6 to 2.0 of low M-singular value decomposition (M-SVD) values. In addition, the proposed approach outperforms conventional image watermarking approach in terms of normalized correlation (NC) values against several image processing attacks including noise addition, filtering, cropping, and JPEG compression.