• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1125-1132
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• 2004

In this Paper, we Propose an effective boundary matching based error detection algorithm using causal neighbor blocks to improve video quality degraded from channel error in block-coded video. The proposed algorithm first calculates boundary mismatch powers between a current block and each of its causal neighbor blocks. It then decides that a current block should be normal if all the mismatch powers are less than an adaptive threshold, which is adaptively determined using the statistics of the two adjacent blocks. In some experiments under the environment of 16bi1s burst error at bit error rates (BERs) of 10$^{-3}$ -10$^{-4}$ , it is shown that the proposed algorithm yields the improvements of maximum 20% in error detection rate and of maximum 3.5㏈ in PSNR of concealed kames, compared with Zeng's error detection algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.31-39
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• 2003

The MPEG-2 source coding algorithm is very sensitive to transmission errors due to using of variable-length coding. When the compressed data are transmitted, transmission errors are generated and error correction scheme is not able to be corrected well them. In the decoder error concealment (EC) techniques must be used to conceal errors and it is able to minimize degradation of video quality. The proposed algorithm is method to conceal successive macroblock errors of I-frame and utilize temporal information of B-frame and spatial information of P-frame In the previous GOP which is temporally the nearest location to I-frame. This method can improve motion distortion and blurring by temporal and spatial errors which cause at existing error concealment techniques. In network where the violent transmission errors occur, we can conceal more efficiently severe slice errors. This algorithm is Peformed in MPEG-2 video codec and Prove that we can conceal efficiently slice errors of I-frame compared with other approaches by simulations.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.15-22
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• 2003

A film scanner is one of the input devices for ac acquiring high resolution and high qualify of digital images from the existing optical film. Recently the demand of film scanners have risen for experts of image printing and editing fields. However, due to the nonlinear characteristic of light source and sensor, colors of the original film image do not correspond to the colors of the scanned image. Therefore color correction for the scanned digital image is essential in film scanner. In this paper, neural network method is applied for the color correction to CIE L/sup *//a/sup *//b/sup */ color model data converted from RGB color model data. Also a film scanner hardware with 12 bit color resolution for each R, G, B and 2400 dpi is implemented by using the TMS320C32 DSP chip and high resolution line sensor. An experimental result shows that the average color correction rate is 79.8%, which is an improvement of 43.5% than our previous method, polygonal regression method.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.485-492
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• 2007

In this paper, we propose the receiver block error detection of the video codec and the image concealment algorithm using fuzzy inference. The proposed error detection and concealment algorithm gets SSD(Summation of Squared Difference) and BMC(Boundary Matching Coefficient) using the temporal and spatial similarity between corresponded blocks in the two successive frames. Proportional constant, ${\alpha}$, for threshold value, TH1 and TH2, is decided after fuzzy data is generated by each parameter. To examine the propriety of the proposed algorithm, random errors are inserted into the QCIF Susie standard image, then the error detection and concealment performance is simulated. To evaluate the efficiency of the algorithm, image quality is evaluated by PSNR for the error detection and concealed image by the existing VLC table and by the proposed method. In the experimental results, the error detection algorithm could detect all of the inserted error, the image quality is improved over 15dB after the error concealment compare to existing error detection algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.128-137
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• 2012

When a CCD camera acquires images in the low light level environment, not only the image signals but also noise components are amplified by the AGC (auto gain control) circuit. Since the noise level in the images acquired in the dark is very high, it is difficult to remove noise with existing denoising algorithms that are targeting the images taken in the normal light condition. In this paper, we proposed an adaptive denoising algorithm that can efficiently remove significant noises caused by the low light level. First, the window including a target pixel is transformed to the frequency domain. Then the algorithm compares the characteristics of equally divided four frequency bands. Finally the noises are adaptively removed according to the frequency characteristics. The proposed algorithm successfully improves the quality of low light level images than the existing algorithms do.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.165-170
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• 2015

The unsharp mask technique emphasize the boundary of the image by adding the boundary of the original image. This technique improves quality by emphasize its boundaries but produce rough image from image noise. The multi channel unsharp mask is possible to enhance entire contrast of the image by applying at least two channels of unsharp mask. However, There is limitations to strengthen boundaries even if the scale strongly applies the multi channel unsharp mask technique. To solve this problem, linear scaling to nonlinear scaling by applying exponential function to existing multi channel unsharp mask technique. Experimental results show enhanced contrast for desired area because of control scaling in details compared with existing unsharp mask technique.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.498-508
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• 2001

In this paper, we propose an efficient coding algorithm for the zoom images to find the optimal depth and texture information. The proposed algorithm is the area-based method consisting of two consecutive steps, i) the depth extraction step and ii) the texture extraction step. The X-Y plane of the object space is divided into triangular patches and the depth value of the node is determined in the first step and then the texture of the each patch is extracted in the second step. In the depth extraction step, the depth of the node is determined by applying the block-based disparity compensation method to the windowed area centered at the node. In the second step, the texture of the triangular patches is extracted from the zoom images by applying the affine transformation based disparity compensation method to the triangular patches with the depth value extracted from the first step. To improve the quality of image, the interpolation is peformed on the object space instead of the interpolation on the image plane.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.149-159
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• 2001

The conventional block-based motion prediction suffers, especially in low bit-rate video application, from shortcomings such as blocking artifacts of motion field and unstable motion estimation. To overcome the deficiency, this paper proposes one method of adopting a new motion compensation scheme based on the irregular triangular mesh structure while keeping the current block-based DCT coding structure of H.263 as much as possible. To represent the reconstructed previous frame using minimal number of control points, the proposed method designs content-adaptive irregular triangular meshes, and then, estimate the motion vector of each control point using the affine transformation-based matching. The predicted current frame is obtained by applying the affine transformation to each triangular mesh. Experiment with the several real video sequences shows improvement both in objective and subjective picture quality over the conventional block-based H.263 method.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.242-251
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• 2020

Recently, many deep convolutional neural networks for image super-resolution have been studied. Existing deep learning-based super-resolution algorithms are architecture that up-samples the resolution at the end of the network. The post-upsampling architecture has an inefficient structure at large scaling factor result of predicting a lot of information for mapping from low-resolution to high-resolution at once. In this paper, we propose a single image super-resolution using Channel Attention Residual Dense Block based on an iterative up-down sampling architecture. The proposed algorithm efficiently predicts the mapping relationship between low-resolution and high-resolution, and shows up to 0.14dB performance improvement and enhanced subjective image quality compared to the existing algorithm at large scaling factor result.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.379-388
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• 2005

Image steganography Is a secret communication scheme to transmit a secret message, which is embedded into an image. The original image and the embedded image are called the cover image and the stego image, respectively. In other words, a sender embeds a secret message into a cover image and transmits a stego image to a receiver, while the receiver takes the stego image, extracts the message from it, and reads the message. General requirements for steganography are great capacity of secret messages, imperceptibility of stego images, and confidentiality between a sender and a receiver. In this paper, we propose a method for being satisfied with three requirements. In order to hide a secret message into a cover image safely, we use a difference value of two consecutive pixels and a secret quantization range. The former is used for the imperceptibility and the latter for the confidentiality. Furthermore, the number of insertion bits is changed according to the difference value for the imperceptibility. Through experiments, we have shown that our method is more good quality of stego images than many other related methods and increases the amount o( message insertion by performing dual insertion processing for some pixels.