• Korean Journal of Remote Sensing
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• v.26 no.4
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• pp.395-401
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• 2010

Image enhancement algorithm aims to improve the visual quality of low contrast image through eliminating the noise and blurring, increasing contrast, and raising detail. This paper proposes adaptive dynamic range linear stretching(ADRLS) algorithm based on advantages of existing methods. ADRLS method is focused on generating sub-histograms of the majority through partitioning the histogram of input image and applying adaptive scale factor. Generated sub-histograms are finally applied by linear stretching(LS) algorithm. In order to validate proposed method, it is compared with LS and histogram equalization(HE) algorithm generally used. As the result, the proposed method show to improve contrast of input image and to preserve distinct characteristics of histogram by controlling excessive change of brightness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.675-681
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• 2019

Noise removal is a pre-requisite procedure in image processing, and various methods have been studied depending on the type of noise and the environment of the image. However, for image processing with high-frequency components, conventional additive white Gaussian noise (AWGN) removal techniques are rather lacking in performance because of the blurring phenomenon induced thereby. In this paper, we propose an algorithm to minimize the blurring in AWGN removal processes. The proposed algorithm sets the high-frequency and the low-frequency component filters, respectively, depending on the pixel properties in the mask, consequently calculating the output of each filter with the addition or subtraction of the input image to the reference. The final output image is obtained by adding the weighted data calculated using the standard deviations and the Gaussian distribution with the output of the two filters. The proposed algorithm shows improved AWGN removal performance compared to the existing method, which was verified by simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1076-1079
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• 2009

This article deals with an optical image stabilizer which moves an image sensor in the direction of cancelling the vibration caused by hand shaking to prevent a photographed image from blurring. The ball-guide way method adopted as a transfer device of the image sensor is easy to be manufactured because of its simple structure and is suitable to minimize the friction between mechanisms, but has weakness of a chance of physical defect such as groove and rising. In case that the movement of the transfer device equipped with the image sensor is blunted because a ball is stuck in defects of guide way, the performance of the image stabilizer falls down drastically. We propose a method to prevent the transfer device from blunting by applying artificial vibration. At this time, the artificial vibration should be designed under consideration of dynamic characteristics and specifications of the system to be discriminated from the vibration caused by hand shaking.

• The Journal of Korea Robotics Society
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• v.5 no.4
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• pp.367-376
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• 2010

This Paper Proposes A Robust Image Stabilization System For A Mobile Robot Using An Extended Kalman Filter (Ekf). Though Image Information Is One Of The Most Efficient Data Used For Robot Navigation, It Is Subjected To Noise Which Is The Result Of Internal Vibration As Well As External Factors Such As Uneven Terrain, Stairs, Or Marshy Surfaces. The Camera Vibration Deteriorates The Image Resolution By Destroying The Image Sharpness, Which Seriously Prevents Mobile Robots From Recognizing Their Environment For Navigation. In This Paper, An Inclinometer Was Used To Measure The Vibration Angle Of The Camera System Mounted On The Robot To Obtain A Reliable Image By Compensating For The Angle Of The Camera Vibration. In Addition The Angle Prediction Obtained By Using The Ekf Enhances The Image Response Analysis For Real Time Performance. The Experimental Results Show The Effectiveness Of The Proposed System Used To Compensate For The Blurring Of The Images.

• Journal of the Chungcheong Mathematical Society
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• v.25 no.2
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• pp.367-377
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• 2012

The goal of the image restoration is to find a good approximation of the original image for the degraded image, the blurring matrix, and the statistics of the noise vector given. Fast truncated Lagrange (FTL) method has been proposed by G. Landi as a image restoration method for large-scale ill-conditioned BTTB linear systems([3]). We implemented FTL method for the image restoration problem with reflective boundary condition which gives better reconstructions of the unknown, the true image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8C
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• pp.811-820
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• 2003

In this paper, multi-watermarking algorithm is proposed to satisfy two purpose of ownership protection and tamper proofing simultaneously. At first, for robust watermarking, the location of the embedding wavelet coefficient is selected by using existing QSWT algorithm. And then, we propose the method inserting discrete cosine transformed watermark. The watermarked image is watermarked again for the tamper proofing. The tamper proofing algorithm is also proposed. According to the experimental results, the proposed multi-watermarking algorithm is robust to the attack, such as blurring, sharpening, JPEG compression. And also, the tampered area are detected in blocks, making it simple to judge which pixels are changed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.207-209
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• 2021

In recent years, with the development of artificial intelligence and IoT technology, automation and unmanned technology are in progress in various fields, and the importance of image processing such as object tracking, medical images and object recognition, which are the basis of this, is increasing. In particular, in systems requiring detailed data processing, noise reduction is used as a pre-processing step, but the existing algorithm has a disadvantage that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using modified spatial weights to minimize information loss in the filtering process. The proposed algorithm uses mask matching to remove AWGN, and obtains the output of the filter by adding or subtracting the output of the modified spatial weight. The proposed algorithm has superior noise reduction characteristics compared to the existing method and reconstructs the image while minimizing the blurring phenomenon.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.462-467
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• 2002

A new approach for reducing the blocking artifact is proposed in this paper. This method can be applied to conventional transform coding, without introducing additional information or significant blurring. Main drawbacks of the Discrete Cosine Transform(DCT) are visible block boundaries due to coarse quantization of the coefficients. Therefore, restoration techniques result in unnecessary blurring of the image. The proposed deblocking algorithm is based on the heuristic approach for edge detection. All edges of the standard still images are categorized, and the best edges are selected. Several images are used fer experiments, and several other previous algorithms are compared with the proposed approach. The results show that the proposed algorithm works better than those of other previous researches. This algorithm can be used for JPEG, MPEG, and H.261 standard images.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.799-802
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• 2000

There are many methods that extract the depth information based on the blurring ratio for object point in DFD(Depth from Defocus). However, it is often difficult to measure the depth of the object in two-dimensional images that was affected by various elements such as edges, textures, and etc. To solve the problem, new DFD method employing the texture classification with a neural network is proposed. This method extracts the feature of texture from an evaluation window in an image and classifies the texture class. Finally, It allocates the correspondent value for the blurring ratio. The experimental result shows that the method gives more accurate than the previous methods.

• 전기의세계
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• v.31 no.3
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• pp.204-208
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• 1982

The objective of this paper is to present a digital method for improving the lateral resolution of the B-scan images in the medical applications of ultrasound. The method is based upon a mathematical model of the lateral blurring caused by the finite beam width of the transducers. This model provides a simple method of applying a recursive scheme for image restoration with fast computation time. The point spread function (P.S.F.) can be measured by the reflective signals after scanning the small pins located along the depth of interest. From the measured P.S.F., one can compute the coefficient matrices of the inverse discrete-time dynamic state variable equation of the blurring process. Then, a recursive scheme for deblurring is applied to the recorded B-scan to improve the lateral resolution. One major advantage of the present recursive scheme over the transform method is in its applicability for the space-variant imaging, such as in the case of the rotational movement of transducer.