• Journal of the Korea Computer Graphics Society
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• v.30 no.2
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• pp.11-19
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• 2024

Demand for small biomimetic robots that can carry out reconnaissance missions without being exposed to the enemy in underground spaces and narrow passages is increasing in order to increase the fighting power and survivability of soldiers in wartime situations. A small compound eye image sensor for environmental recognition has advantages such as small size, low aberration, wide angle of view, depth estimation, and HDR that can be used in various ways in the field of vision. However, due to the small lens size, the resolution is low, and the problem of resolution in the fused image obtained from the actual compound eye image occurs. This paper proposes a compound eye image quality enhancement algorithm based on Image Enhancement and ESRGAN to overcome the problem of low resolution. If the proposed algorithm is applied to compound eye image fusion images, image resolution and image quality can be improved, so it is expected that performance improvement results can be obtained in various studies using compound eye cameras.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.325-333
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• 2010

Image registration involves overlapping images of an identical region and assigning the data into one coordinate system. Image registration has proved important in remote sensing, enabling registered satellite imagery to be used in various applications such as image fusion, change detection and the generation of digital maps. The image descriptor, which extracts matching points from each image, is necessary for automatic registration of remotely sensed data. Using contrast enhancement algorithms such as histogram equalization and image stretching, the normalized data are applied to the image descriptor. Drawing on the different spectral characteristics of high resolution satellite imagery based on sensor type and acquisition date, the applied normalization method can be used to change the results of matching interest point descriptors. In this paper, the matching points by scale invariant feature transformation (SIFT) are extracted using various contrast enhancement algorithms and injection of Gaussian noise. The results of the extracted matching points are compared with the number of correct matching points and matching rates for each point.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.31-41
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• 2009

The Image sensor of digital still camera has a limited dynamic range. In high dynamic range scenes, a picture often turns out to be underexposed or overexposed. Retinex algorithm based on the theory of the human visual perception is known to be effective contrast enhancement technique. However, it happens the unbalanced contrast enhancement which is the global contrast increased, and the local contrast decreased in the high dynamic range scenes. In this paper, to enhance the both global and local contrast, we propose the weight mapping retinex algorithm. Weight map is composed of the edge and exposure data which are extracted in the each retinex image, and merged with the retinex images in the fusion processing. According to the output picture comparing and numerical analysis, the proposed algorithm gives the better output image with the increased global and local contrast.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5112-5129
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• 2019

Image enhancement is a challenging problem in the field of image processing, especially low-light color images enhancement. This paper proposed a robust and comprehensive enhancement method based several points. First, the idea of bright channel is introduced to estimate the illumination map which is used to attain the enhancing result with Retinex model, and the color constancy is keep as well. Second, in order eliminate the illumination offsets wrongly estimated, morphological closing operation is used to modify the initial estimating illumination. Furthermore, in order to avoid fabricating edges, enlarged noises and over-smoothed visual features appearing in enhancing result, a multi-scale closing operation is used. At last, in order to avoiding the haloes and artifacts presented in enhancing result caused by gradient information lost in previous step, guided filtering is introduced to deal with previous result with guided image is initial bright channel. The proposed method can get good illumination map, and attain very effective enhancing results, including dark area is enhanced with more visual features, color natural and constancy, avoiding artifacts and over-enhanced, and eliminating Incorrect light offsets.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.97-107
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• 2015

The initial X-ray images obtained from a digital X-ray machine have a wide data range and uneven brightness level than normal images. In particular, in Chest X-ray images, it is necessary to improve naturally all of the parts such as ribs, spine, tissue, etc. These X-ray images can not be improved enough from conventional image quality enhancement algorithms because their characteristics are different from ordinary images'. This paper proposes to eliminate unnecessary background from an input image and expand the histogram range of the image. Then, we adjust the weight per frequency band of the image for improvement of contrast and sharpness. Finally, jointly taking the advantages of global contrast enhancement and local contrast enhancement methods we obtain an improved X-ray image suitable for effective diagnosis in comparison with the existing methods. Experimental results show quantitatively that the proposed algorithm provides better X-ray images in terms of the discrete entropy and saturation than the previous works.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.73-81
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• 2016

In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.15-20
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• 2008

High-spatial resolution remote sensing satellites (IKONOS-2, QuickBird and KOMPSAT-2) have provided low-spatial resolution multispectral images and high-spatial resolution panchromatic images. Image fusion or Pan-sharpening is a very important in that it aims at using a satellite image with various applications such as visualization and feature extraction through combining images that have a different spectral and spatial resolution. Many image fusion algorithms are proposed, most methods could not preserve the spectral information of original multispectral image after image fusion. In order to solve this problem, modified induction technique which reduce the spectral distortion of fused image is developed. The spectral distortion is adjusted by the comparison between the spatially degraded pan-sharpened image and original multispectral image and our algorithm is evaluated by QuickBird satellite imagery. In the experiment, pan-sharpened image by various methods can reduce spectral distortion when our algorithm is applied to the fused images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.65-73
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• 2011

In this paper, we present a novel digital multifocusing approach using adaptive region-based histogram equalization for the multiple color-filter aperture (MCA) system with insufficient amount of incoming light. From the image acquired by the MCA system, we can estimate the depth information of objects at different distances by measuring the amount of misalignment among the RGB color planes. The estimated depth information is used to obtain multifocused images together with the process of the region-of-interests (ROIs) classification, registration, and fusion. However, the MCA system results in the low-exposure problem because of the limited size of the apertures. For overcoming this problem, we propose adaptive region-based histogram equalization. Based on the experimental results, the proposed algorithm is proved to be able to obtain in-focused images under the low light level environment.

• Journal of Korea Multimedia Society
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• v.21 no.9
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• pp.1044-1051
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• 2018

In this paper, we propose a new method to improve low light image. In order to improve the image quality of a night image with a moving object as much as the quality of a daytime image, the following tasks were performed. Firstly, we reduce the noisy of the input night image and improve the night image by the tone mapping method. Secondly, we segment the input night image into a foreground with motion and a background without motion. The motion is detected using both the difference between the current frame and the previous frame and the difference between the current frame and the night background image. The background region of the night image takes pixels from corresponding positions in the daytime image. The foreground regions of the night image take the pixels from the corresponding positions of the image which is improved by the tone mapping method. Experimental results show that the proposed method can improve the visual quality more clearly than the existing methods.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.550-558
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• 2013

The infrared and visible images are represented by different information due to the different wavelength of the light. The infrared image has thermal information and the visible image has texture information. Desirable results are obtained by fusing infrared and visible information. To enhance a visible image, we extract a weight map from a visible image using saturation, brightness. After that, the weight map is adjusted using thermal information in the infrared image. Finally, an enhanced image is resulted from combining an infrared image and a visible image. Our experiment results show that our proposed algorithm is working well to enhance the smoke in the original image.