• Journal of Internet Computing and Services
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• v.11 no.2
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• pp.99-107
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• 2010

In this paper a blind watermarking algorithm for digital image is presented. The proposed method operates in wavelet domain. The watermark is decomposed into 2D-IMFs using BEMD which is the 2-dimensional extension of 1 dimensional empirical mode decomposition. The CDMA based on SS technique is applied to watermark embedding and detection process. In the watermark embedding process, each IMF of watermark is embedded into middle frequency subimages in wavelet domain, so subimages just include partial information about embedded watermark. By characteristics of BEMD, when the partial information of watermark is synthesized, the original watermark is reconstructed. The experimental results show that the proposed watermarking algorithm is imperceptible and moreover is robust against JPEG compression, common image processing distortions.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.53-65
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• 2002

The most widespread techniques for DEM generation are stereoscopy for optical sensor images and SAR interferometry(InSAR) for SAR images. These techniques suffer from certain sensor and processing limitations, which can be overcome by the synergetic use of both sensors and DEMs respectively. This study is associated with improvements of accuracy with consistency of image's characteristics between two different DEMs coming from stereoscopy for the optical images and interferometry for SAR images. The MWD(Multiresolution Wavelet Decomposition) and HPF(High-Pass Filtering), which take advantage of the complementary properties of SAR and stereo optical DEMs, will be applied for the fusion process. DEM fusion is tested with two sets of SPOT and ERS-l/-2 satellite imagery and for the analysis of results, DEM generated from digital topographic map(1 to 5000) is used. As a result of an integration of DEMs, it can more clearly portray topographic slopes and tilts when applying the strengths of DEM of SAR image to DEM of an optical satellite image and in the case of HPF, the resulting DEM.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.143-148
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• 2008

A real-time face detection is to find human faces robustly under the cluttered background free from the effect of occlusion by other objects or various lightening conditions. We propose a face detection system for real-time applications using wavelet decomposition method based on Gabor features. Firstly, skin candidate regions are extracted from the given image by skin color filtering and projection method. Then Gabor-feature based template matching is performed to choose face cadidate from the skin candidate regions. The chosen face candidate region is transformed into 2-level wavelet decomposition images, from which feature vectors are extracted for classification. Based on the extracted feature vectors, the face candidate region is finally classified into either face or nonface class by the Levenberg-Marguardt back-propagation neural network.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.366-373
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• 2016

This paper proposes a pre-processing algorithm to improve the coding efficiency of perceptual video coding. First, an input image is decomposed into multiple sub-bands through linear sub-band decomposition. Then, the sub-bands that have low visual sensitivity are suppressed by assigning small gains to them. Experimental results show that if the proposed algorithm is adopted for pre-processing in a High Efficiency Video Coding (HEVC) encoder, it can provide significant bit-saving effects of approximately 12% in low delay mode and 9.4% in random access mode.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.595-598
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• 2004

In this paper, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D mage into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that the primitive elements are extracted too much to represent the shape and the processing time is long. To solve these problems, a new shape decomposition algorithm using the 8 bit planes obtained from gray code is proposed.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.89-92
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• 2000

In this paper, an effective image restoration using Genetic Algorithm(GA) in wavelet transform region is proposed. First, a wavelet transform is used for decomposition of a blurred image with white Gaussian noise as a preprocessing of the proposed method. The wavelet transform decomposes a degraded image into a wavelet subband coefficient planes. In this wavelet transformed subband coefficient planes, three highest subbands is composed entirely of noise elements on a degraded image. So, these subbands are removed. And remained subbands except for the lowest subband are individually applied to GA. For the performance evaluation, the proposed method is compared with a conventional single GA algorithm and a conventional hybrid method of wavelet transform and GA for a Lenna image and a boat image. As an experimental result, the proposed algorithm is prior to a conventional methods as each PSNR 3.4dB, 1.3dB.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.192-195
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• 2003

This paper is a study on the psuedocolor image enhancement of infrared image using B-spline wavelet transform. The psuedocolor enhancement is that the frequency lose on the minimum, the decomposition enhancement is realized by B-spline and RGB image is extracted by wavelet transform. The result of experiment increases enhanced infrared image as 3dB by processing of B-spline and wavelet transform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3620-3637
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• 2019

Since the birth of Synthetic Aperture Radar (SAR), it has been widely used in the military field and so on. However, the existence of speckle noise makes a good deal inconvenience for the subsequent image processing. The continuous development of sparse representation (SR) opens a new field for the speckle suppressing of SAR image. Although the SR de-noising may be effective, the over-smooth phenomenon still has bad influence on the integrity of the image information. In this paper, one novel SAR image de-noising method based on residual image fusion and sparse representation is proposed. Firstly we can get the similar block groups by the non-local similar block matching method (NLS-BM). Then SR de-noising based on the adaptive K-means singular value decomposition (K-SVD) is adopted to obtain the initial de-noised image and residual image. The residual image is processed by Shearlet transform (ST), and the corresponding de-noising methods are applied on it. Finally, in ST domain the low-frequency and high-frequency components of the initial de-noised and residual image are fused respectively by relevant fusion rules. The final de-noised image can be recovered by inverse ST. Experimental results show the proposed method can not only suppress the speckle effectively, but also save more details and other useful information of the original SAR image, which could provide more authentic and credible records for the follow-up image processing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.269-274
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• 2021

In secret communication, steganography is the sending and receiving of secret messages without being recognized by a third party. In the spatial domain method bitwise information is inserted into the virtual bit plane of the decomposed pixel values of the image. That is, the bitwise secret message is sequentially inserted into the least significant bit(LSB) of the image, which is a cover medium. In terms of application, the LSB is simple, but has a drawback that can be easily detected by a third party. If the upper bit plane is used to increase security, the image quality may deteriorate. In this paper, I present a method for concealing Hangul secret messages in image steganography based on the lo-th bit plane and the decomposition of modified pixel intensity values. After decomposing the Hangeul message to be hidden into choseong, jungseong and jongseong, then a shuffling process is applied to increase confidentiality and robustness. PSNR was used to confirm the efficiency of the proposed method. It was confirmed that the proposed technique has a smaller effect in terms of image quality than the method applying BCD and Fibonacci when inserting a secret message in the upper bit plane. When compared with the reference value, it was confirmed that the PSNR value of the proposed method was appropriate.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.499-507
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• 2016

Medical imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Ultrasound (US) produce a large amount of digital medical images. Hence, compression of digital images becomes essential and is very much desired in medical applications to solve both storage and transmission problems. But at the same time, an efficient image compression scheme that reduces the size of medical images without sacrificing diagnostic information is required. This paper proposes a novel threshold-based medical image compression algorithm to reduce the size of the medical image without degradation in the diagnostic information. This algorithm discusses a novel type of thresholding to maximize Compression Ratio (CR) without sacrificing diagnostic information. The compression algorithm is designed to get image with high optimum compression efficiency and also with high fidelity, especially for Peak Signal to Noise Ratio (PSNR) greater than or equal to 36 dB. This value of PSNR is chosen because it has been suggested by previous researchers that medical images, if have PSNR from 30 dB to 50 dB, will retain diagnostic information. The compression algorithm utilizes one-level wavelet decomposition with threshold-based coefficient selection.