• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.943-949
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• 2019

As use of digital equipment in various fields is increasing importance of processing video and signals is rising as well. However, in the process of sending and receiving signals, noise occurs due to different reasons and this noise bring about a huge influence on final output of the system. This research suggests algorithm for effectively repairing video in consideration to characteristics of its noise in condition where impulse and AWGN noises are combined. This algorithm tries to preserve video features by considering inference to noise components and resolution of filtering mask. Depending on features of input resolution, standard value is set and similar resolutions is selected for noise removal. This algorithm showing simulation result had outstanding noise removal and is compared and analyzed with existing methods by using different ways such as PSNR.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.188-199
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• 2008

In conventional video coding, encoder complexity is much higher than that of decoder. However, investigations for lightweight encoder to eliminate motion prediction/compensation claiming most complexity in encoder have recently become an important issue. The Wyner-Ziv coding is one of the representative schemes for the problem and, in this scheme, since encoder generates only parity bits of a current frame without performing any type of processes extracting correlation information between frames, it has an extremely simple structure compared to conventional coding techniques. However, in Wyner-Ziv coding, channel decoding errors occur when noisy side information is used in channel decoding process. These channel decoding errors appear more frequently, especially, when there is not enough correlation between frames to generate accurate side information and, as a result, those errors look like Salt & Pepper type noise in the reconstructed frame. Since this noise severely deteriorates subjective video quality even though such noise rarely occurs, previously we proposed a computationally extremely light encoding method based on selective median filter that corrects such noise using spatial correlation of a frame. However, in the previous method, there is a problem that loss of texture from filtering may exceed gain from error correction by the filter for video sequences having complex torture. Therefore, in this paper, we propose an improved lightweight encoding method that minimizes loss of texture detail from filtering by allowing information of texture and that of noise in side information to be utilized by the selective median filter. Our experiments have verified average PSNR gain of up to 0.84dB compared to the previous method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.95-105
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• 2003

A novel reference point detection method is proposed by exploiting tile gradient probabilistic model that captures the curvature information of fingerprint. The detection of reference point is accomplished through searching and locating the points of occurrence of the most evenly distributed gradient in a probabilistic sense. The uniformly distributed gradient texture represents either the core point itself or those of similar points that can be used to establish the rigid reference from which to map the features for recognition. Key benefits are reductions in preprocessing and consistency of locating the same points as the reference points even when processing arch type fingerprints. Moreover, the new feature extraction method is proposed by improving the existing feature extraction using filterbank method. Experimental results indicate the superiority of tile proposed scheme in terms of computational time in feature extraction and verification rate in various noisy environments. In particular, the proposed gradient probabilistic model achieved 49% improvement under ambient noise, 39.2% under brightness noise and 15.7% under a salt and pepper noise environment, respectively, in FAR for the arch type fingerprints. Moreover, a reduction of 0.07sec in reference point detection time of the GPM is shown possible compared to using the leading the poincare index method and a reduction of 0.06sec in code extraction time of the new filterbank mettled is shown possible compared to using the leading the existing filterbank method.

• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.417-429
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• 2010

Reversible watermarking inserts watermark into digital media in such a way that visual transparency is preserved and then enables to restore the original media from the marked one without any loss of media quality. This watermarking can be applied to quality-sensitive imaging such as medical imaging, military imaging, remote-sensing imaging, and precious artwork, where the original media should be preserved during image processing and analysis. In this paper, a reversible image watermarking technique that embeds message bits by modifying the differential histogram of adjacent pixels is presented. In order to satisfy both high embedding capacity and visual quality, the proposed technique exploits the fact that adjacent pixels in the image have highly spatial correlation. Also, we prevent overflow/underflow problem and salt-and-pepper artifacts by employing a predicted error compensation scheme. Through experiments using various test images, we prove that the presented technique provides perfect reversibility and high embedding capacity, while maintaining the induced-distortion low.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.93-99
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• 2024

The digital medical imaging, especially, computed tomography (CT), should necessarily be considered in terms of noise distribution caused by converting to X-ray photon to digital imaging signal. Recently, the denoising technique based on deep learning architecture is increasingly used in the medical imaging field. Here, we evaluated noise reduction effect according to various noise types based on the U-net deep learning model in the lung CT images. The input data for deep learning was generated by applying Gaussian noise, Poisson noise, salt and pepper noise and speckle noise from the ground truth (GT) image. In particular, two types of Gaussian noise input data were applied with standard deviation values of 30 and 50. There are applied hyper-parameters, which were Adam as optimizer function, 100 as epochs, and 0.0001 as learning rate, respectively. To analyze the quantitative values, the mean square error (MSE), the peak signal to noise ratio (PSNR) and coefficient of variation (COV) were calculated. According to the results, it was confirmed that the U-net model was effective for noise reduction all of the set conditions in this study. Especially, it showed the best performance in Gaussian noise.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.25-35
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• 2022

The SAP(salt-and-pepper) noise changes the pixel value to the maximum and minimum values of the dynamic region of the pixel. For this reason, unlike white Gaussian noise, SAP noise can predict the ratio of noise relatively easily. Because the condition of the neighboring pixels that can be referenced changes according to the noise ratio, it is necessary to apply different noise reduction methods according to the noise ratio. This paper proposes an adaptive switching filtering algorithm which can eliminates the SAP noise. It consists of two phases. It first detects the location of the SAP noise and calculates the noise ratio. After that, the image is reconstructed using different methods depending on which of the three sections the calculated noise ratio belongs to. As a result of the experiment, the proposed method showed superior objective and subjective image quality compared to the previous methods such as MF, AFSWMF, NAMF and RWMF.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.455-458
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• 2008

Former times Information Technology generally has only depended on text or sound, while nowadays information is being moved through a variety of image media. Cell phone, TV and computer have been major elements of modem society as mediators using image signal. Therefore, image signal processing also has been treated importantly and done actively. The processing has been developed in many fields of digital image processing technologies as image data compression, recognition, restoration, etc. Noises are inevitably generated by using the signals during the processing, and typical types of the noise are Impulse(salt & pepper) and AWGN(Addiction White Gaussian Noise). To reduce the noise, various kinds of filters have been developed, and according to each noise, it is being used different filter each. However, the noise is not generated by one signal but by a complex. In this paper, I suggested an image filter to remove the complex noise, and compared with existing filters' methods for verification.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.19-26
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• 2005

Image interpolation in the wavelet domain usually takes advantage of the probabilistic models for the intrascale statistics and the interscale dependency. In this paper, we adopt the linear model for the absolute values of wavelet coefficients of interpolated image across scale to estimate the variances of extrapolated bands. The proposed algorithm uses randomly generated wavelet coefficients based on the estimated parameters for probabilistic model. Random number generation according to the estimated probabilistic model may induce the 'salt and pepper' noise in subbands. We reduce the noise power by Wiener filtering. We observe that the proposed method generates the histogram of the subband coefficients similar to the that of original image. Experimental results show that our method outperforms the previous wavelet-domain interpolation method as well as the conventional bicubic method.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.97-103
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• 2010

In this paper, we propose a new digital watermarking technique. The main idea of the proposed algorithm relies on the assumption that any real number can be expressed as a summation of the exponential form with base of 2 and if only consider the first few summations some numbers can be expressed in the same form. Therefore, we can be sure that some amount of changes does not affect the first few summations. The algorithm decomposes a host image in wavelet domain and intensity of the significant wavelet coefficient is expressed in exponential form with base of 2. Multiple barcode watermarks are then embedded by modifying the parity of the exponent. The proposed scheme is semi-blind and also offers either objective or subjective deteew su as well. From extracted watermarks, more accurate watermark is obtained by merging technique as a final watermark. As a simulation result, the proposed algorithm could resist most cases of salt and pepper noise, Gaussian noise and JPEG compression.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.21-31
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• 2017

In this paper, the Zynq system-on-chip (SoC) platform is used to design an adaptive noise reduction and edge-detection system using partial reconfiguration. Filters are implemented in a partially reconfigurable (PR) region to provide high computational complexity in real-time, 1080p video processing. In addition, partial reconfiguration enables better utilization of hardware resources in the embedded system from autonomous replacement of filters in the same PR region. The proposed edge-detection system performs adaptive noise reduction if the noise density level in the incoming video sequences exceeds a given threshold value. Results of implementation show that the proposed system improves the accuracy of edge-detection results (14~20 times in Pratt's Figure of Merit) through self-reconfiguration of filter bitstreams triggered by noise density level in the video sequences. In addition, the ZyCAP controller implemented in this paper enables about 2.1 times faster reconfiguration when compared to a PCAP controller.