• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.67-72
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• 2012

In this paper, we present an image enhancement method for atmospherically degraded images using atmospheric light and transmission based on color analysis. We first generate a normalized image using maximum value of each RGB color channel. Then, each atmospheric light is estimated from RGB color channel respectively by calculating reflectance of an image. We also, generate a transmission using gamma coefficients from the Y channel of the image. We can significantly enhance the visibility of an image by using the estimated atmospheric light and the transmission. The proposed algorithm can remove atmospheric degradation components better than existing techniques because the color prevents color distortion which is common problem of existing techniques. Experimental results demonstrate that the proposed algorithm can improve visibility be removing fog, smoke, and dust.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.1
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• pp.1-8
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• 2020

The thermal image device support image to detect infrared light from the object without light. It can use not only defence-related industry, but also civilian industry. This paper presents a new thermal image processing module using common image processor. The proposed module shows 10~20% performance improvement with normal mode and 50% performance improvement with sleep mode compared with the previously thermal image module based FPGA. and it guarantees high scalability according to modular system. In addition, the proposed module improves modulation and reuse, so it expect to have reduction of development period, low development cost. various application. In addition, it expect to have satisfaction of customer requirements, development design, development period, release date of product.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.119-128
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• 2014

This paper presents a new method for improving the quality of images corrupted by an external source that generates an attenuation and scattering of light like dust, water droplets and fog. Conventional defog methods typically encounter a distortion such that the restored image has low contrast and oversaturation of color in some regions because of the mis-estimated airlight and wrong media transmission. Therefore, in order to mitigate these problems, we propose a robust airlight selection method and local saturation evaluation method for estimating media transmission. The proposed method addresses the wrong media transmission and over-saturation problems caused by the mis-estimated airlight and thereby improves the restored image quality. The results of relevant experiments of the proposed method against conventional ones confirm the improved accuracy of atmospheric light estimation and the quality of restored images with regard to objective and subjective performance measures.