• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.37-45
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• 2007

We propose an adaptive image enhancement method for epigraphic images, which is based on local statistics. Local statistics of the image are utilized for adaptive realization of the enhancement, that controls the contribution of the smoothing or sharpening paths. Image contrast enhancement occurs in details and noises are suppressed in smooth areas. For modeling the epigraphic image, pre~process is achieved by HSDI(Hanzi squeezed digital image). We have calculated the local statistics from this HSDI model. Application of this approach to HSDI has shown that processing not only smooths the background areas but also improves the subtle variations of edges, so that the word regions can be enhanced. Experimental results show that the proposed algorithm has better performance than the conventional image enhancement ones.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1479-1481
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• 2003

The aim of this paper was mainly to interpret the real information-missing patch of image by using the kriging interpolation technology of spatial statistics. The TM Image of the Jingouling Forest Farm of Wangqing Forestry Bureau of Northeast China on 1 July 1997 was used as the tested material in this paper. Based on the classification for the TM image, the information pixel-missing patch of image was interpolated by the kriging interpolation technology of spatial statistics theory under the image treatment software-ERDAS and the geographic information system software-Arc/Info. The interpolation results were already passed precise examination. This paper would provide a method and means for interpreting the information-missing patch of image.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.3-6
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• 2003

A nonlinear iterative filtering based on local statistics and anisotropic diffusion is introduced. Local statistics determines the diffusion coefficient at each iteration step. Anisotropic diffusion can be seen as estimates a piecewise smooth image from the noisy input image in the experimental section, our results are shown to suppress noise with preserving the edges. Therefore, it enhances the image and improves performance.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.41-51
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• 2014

This paper describes a method to estimate the noise power using the minimum statistics approach, which was originally proposed for audio processing. The proposed minimum statistics-based method separates a noisy image into multiple frequency bands using the three-level discrete wavelet transform. By assuming that the output of the high-pass filter contains both signal detail and noise, the proposed algorithm extracts the region of pure noise from the high frequency band using an appropriate threshold. The region of pure noise, which is free from the signal detail part and the DC component, is well suited for minimum statistics condition, where the noise power can be extracted easily. The proposed algorithm reduces the computational load significantly through the use of a simple processing architecture without iteration with an estimation accuracy greater than 90% for strong noise at 0 to 40dB SNR of the input image. Furthermore, the well restored image can be obtained using the estimated noise power information in parametric image restoration algorithms, such as the classical parametric Wiener or ForWaRD image restoration filters. The experimental results show that the proposed algorithm can estimate the noise power accurately, and is particularly suitable for fast, low-cost image restoration or enhancement applications.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.487-501
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• 2017

A machine vision system (MVS) is a computer system that utilizes one or more image-capturing devices to provide image data for analysis and interpretation. Recently there have been a number of industrial- and medical-device applications where control charts have been proposed for use with image data. The use of image-based control charting is somewhat different from traditional control charting applications, and these differences can be attributed to several factors, such as the type of data monitored and how the control charts are applied. In this paper, we investigate the adjustment effect of image size and region of interest (ROI) size, when we use control charts to monitor grayscale image data in industry.

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.89-92
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• 2017

This paper investigates simple gray level image enhancement technique based on Genetic Algorithms and Local Statistics. The task of GA is to adapt the parameters of local sliding masks over pixels, finding out the best parameters preserving the brightness and possibly preventing the creation of intensity artifacts in the local area of images. The algorithm is controlled by GA as to enhance the contrast and details in the images automatically according to an object fitness criterion. Results obtained in terms of subjective and objective evaluations, show the plausibility of the method suggested here.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.590-599
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• 2018

Multivariate finite mixture model is becoming more and more popular in image processing. Performing image denoising from image patches to the whole image has been widely studied and applied. However, there remains a problem that the structure information is always ignored when transforming the patch into the vector form. In this paper, we study the operator which extracts patches from image and then transforms them to the vector form. Then, we find that some pixels which should be continuous in the image patches are discontinuous in the vector. Due to the poor anti-noise and the loss of structure information, we propose a new operator which may keep more information when extracting image patches. We compare the new operator with the old one by performing image denoising in Expected Patch Log Likelihood (EPLL) method, and we obtain better results in both visual effect and the value of PSNR.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07b
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• pp.1584-1587
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• 2005

Although the picture quality of today's displays is very good already, a continuous improvement is desirable as the new larger display sizes increase the visibility of artifacts. A contributing factor for picture quality enhancement through smart video processing and algorithm design is the information gathered from video statistics. Interesting parameters gathered from video statistics are e.g. the image- and display load, the usage of the color gamut, the estimated power consumption and the occurrence of static image parts. Examples of applications that can benefit from video statistics are power calculations, color gamut mapping algorithms, dynamic backlight control for LCD panels and LED backlights for LCD panels.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.25-32
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• 2000

Digital watermarking has been recently proposed as the means of intellectual property right protection of multimedia data. We present a novel watermarking scheme to hide a copyright information in a digital image. The method Is based on the 2D DWT(Discrete Wavelet Transform) and image statistics. Gaussian and Laplacian noises as the watermarks are added to the large wavelet coefficients at the high and middle frequency bands in the wavelet domain. Experimental results show that the proposed Laplacian watermark is stronger to several common image distortions, such as noises, JPEG coding as different qualities, Gaussian blurring, and edge enhancement.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.382-387
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• 2014

Image retrieval is a procedure to find images based on the resemblance between query image and all images. In retrieving images, the crucial step that arises is how to define the similarity between images. In this paper, we propose a new similarity measure which is based on distribution of color. We apply the new measure to retrieving two different types of images, wallpaper images and the logo of automobiles, and compare its performance to other existing similarity measures.