• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.8
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• pp.369-374
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• 2006

Due to development of internet network environments and data compression techniques, the size and amount of multimedia data has greatly increased. They are compressed before transmission or storage. Dealing with these compressed data such as video retrieval or indexing requires decompression procedure in most cases. This causes additional computations and increases the processing time. In various applications a histogram is one of the most frequently used tools. Efficiency of extracting such histograms will drop down if decompression is involved. We propose a novel scheme for extracting histograms from images that are transformed into the compressed domain by 8x8 DCT(Discrete Cosine Transform). In this scheme an averaged version of original image is obtained by a simple linear combination of DCT coefficients with the sets of coefficients we designed.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.269-272
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• 2007

The shortcut shot detection based on MPEG compressed video bitstream is presented in this paper. The detection algorithm is used the video picture frame from MPEG compressed video directly not to be decompressed the original image. For shortcut detection, I and P frame of MPEG video bitstream are classified. The changing scene cuts at I pictures are detected by the decompressed DC image and scene cuts at P picture frame by monitoring the percentage of intra-macroblocks per P picture are detected. Experimental results using test video bitstream QVGA results in average 92% detection rate, searching time is taken around 4.5 times faster in comparison with changing scene shot detection algorithm which is decompressed the compressed bitstream.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.23-30
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• 2016

In this paper, we propose an adaptive histogram projection technique for dynamic range compression and an efficient detail enhancement method which is enhancing strong edge while reducing noise. First, The high dynamic range image is divided into low-pass component and high-pass component by applying 'guided image filtering'. After applying 'guided filter' to high dynamic range image, second, the low-pass component of the image is compressed into 8-bit with the adaptive histogram projection technique which is using global standard deviation value of whole image. Third, the high-pass component of the image adaptively reduces noise and intensifies the strong edges using standard deviation value in local path of the guided filter. Lastly, the monitor display image is summed up with the compressed low-pass component and the edge-intensified high-pass component. At the end of this paper, the experimental result show that the suggested technique can be applied properly to the IR images of various scenes.

• Korean Journal of Cognitive Science
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• v.11 no.2
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• pp.79-87
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• 2000

In this paper we present a face recognition and face detection algorithm in MPEG compressed video. The proposed method consists three stage of processing steps. The first step is to produce a spatially reduced DC image form MPEG compressed video for processing. And the second step is face detection on reduced DC image. Finally, the last step is face recognition on partially extracted compressed frames which contain the detected faces. The spatially reduced DC image is produced from two dimensional inverse DCT of the DC coefficient and the first two AC coefficients. The face detection is performed on DC image and face recognition is performed on one extracted frame per GOP by using the K-L transform. In order to evaluate the proposed method, we carried out experiments on video database. The experiment results show the proposed method is very efficient and helpful for target tasks.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.1-7
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• 2009

In recent years, compressed sensing (CS) algorithm has been studied in various research areas including medical imaging. To use the CS algorithm, the signal that is to be reconstructed needs to have the property of sparsity But, most medical images generally don't have this property. One method to overcome this problem is by using sparsifying transform. However, MR imaging, compared to other medical imaging modality, has the unique property that by using appropriate image acquisition pulse sequences, the image contrast can be modified. In this paper, we propose the possibility of applying the CS algorithm with non-sparsifying transform to the pulse sequence modified MR images and improve the reconstruction performance of the CS algorithm by using an appropriate sparsifying transform. We verified the proposed contents by computer simulation using Shepp-Logan phantom and in vivo data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1051-1077
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• 2021

The secure communication of information is a major concern over the internet. The information must be protected before transmitting over a communication channel to avoid security violations. In this paper, a new hybrid method called compressed encrypted data embedding (CEDE) is proposed. In CEDE, the secret information is first compressed with Lempel Ziv Welch (LZW) compression algorithm. Then, the compressed secret information is encrypted using the Advanced Encryption Standard (AES) symmetric block cipher. In the last step, the encrypted information is embedded into an image of size 512 × 512 pixels by using image steganography. In the steganographic technique, the compressed and encrypted secret data bits are divided into pairs of two bits and pixels of the cover image are also arranged in four pairs. The four pairs of secret data are compared with the respective four pairs of each cover pixel which leads to sixteen possibilities of matching in between secret data pairs and pairs of cover pixels. The least significant bits (LSBs) of current and imminent pixels are modified according to the matching case number. The proposed technique provides double-folded security and the results show that stego image carries a high capacity of secret data with adequate peak signal to noise ratio (PSNR) and lower mean square error (MSE) when compared with existing methods in the literature.

• Imaging Science in Dentistry
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• v.34 no.3
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• pp.117-122
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• 2004

Purpose : To determine the proper image compression method and ratio without image quality degradation in intraoral digital radiographic images, comparing the discrete cosine transform (DCT)-based JPEG with the wavelet-based JPEG 2000 algorithm. Materials and Methods : Thirty extracted sound teeth and thirty extracted teeth with occlusal caries were used for this study. Twenty plaster blocks were made with three teeth each. They were radiographically exposed using CDR sensors (Schick Inc., Long Island, USA). Digital images were compressed to JPEG format, using Adobe Photoshop v.7.0 and JPEG 2000 format using Jasper program with compression ratios of 5 : 1,9 : 1, 14 : 1,28 : 1 each. To evaluate the lesion detectability, receiver operating characteristic (ROC) analysis was performed by the three oral and maxillofacial radiologists. To evaluate the image quality, all the compressed images were assessed subjectively using 5 grades, in comparison to the original uncompressed images. Results: Compressed images up to compression ratio of 14 : 1 in JPEG and 28 : 1 in JPEG 2000 showed nearly the same the lesion detectability as the original images. In the subjective assessment of image quality, images up to compression ratio of 9 : 1 in JPEG and 14 : 1 in JPEG 2000 showed minute mean paired differences from the original Images. Conclusion : The results showed that the clinically acceptable compression ratios were up to 9 : 1 for JPEG and 14 : 1 for JPEG 2000. The wavelet-based JPEG 2000 is a better compression method, comparing to DCT-based JPEG for intraoral digital radiographic images.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.103-109
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• 2014

This study derived the inter-conversion matrices, which can be used in heterogeneous image transcoding between the compressed images using different transforms, such as the $8{\times}8$ block discrete cosine transform (BDCT) and the one-level discrete wavelet transform (DWT). Basically, to obtain the one-level DWT coefficients from $8{\times}8$ BDCT, inverse BDCT should be performed followed by forward DWT, and vice versa. On the other hand, if the proposed interconversion approach is used, only one inter-conversion matrix multiplication makes the corresponding transcoding possible. Both theoretical and experimental analyses showed that the amount of computation of the proposed approach decreases over 20% when the inter-conversion matrices are used under specific conditions.

• Journal of the Korean Society of Radiology
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• v.15 no.7
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• pp.999-1005
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• 2021

The object of this research is CS, which increases resolution while shortening inspection time, is applied to MRA to compare the quality of images for SENSE and CS techniques and to evaluate SNR and CNR to find out the optimal techniques and to provide them as clinical basic data based on this information. Data were analyzed on 32 patients who performed TOF MRA tests at a university hospital in Chung cheong-do (15 males, 17 females), ICA stenosis:10, M1 Aneurysm:10, and average age 53 ± 4.15). In the inspection, the inspection equipment was Ingenia CX 3.0T, Archieva 3.0T, and 32 channel head coil and 3D gradient echo as a method for equipment data. SNR and CNR of each image were measured by quantitative analysis, and the quality of the image was evaluated by dividing the observer's observation into 5 grades for qualitative evaluation. Imaging evaluation is described as being significant when the p-value is 0.05 or less when the paired T-test and Wilcoxon test are performed. Quantitative analysis of SNR and CNR in TOF MRA images Compared to the SENSE method, the CS method is a method measurement method (p <0.05). As an observer's evaluation, the sharpness of blood vessels: CS (4.45 ± 0.41), overall image quality: CS (4.77 ± 0.18), background suppression of images: CS (4.57 ± 0.18) all resulted in high CS technique (p = 0.000). In conclusion, the Compressed SENSE TOF MRA technique shows superior results when comparing and evaluating the SENSE and Compressed SENSE techniques in increased flow rate magnetic resonance angiography. The results are thought to be the clinical basis material in the 3D TOF MRA examination for brain disease.

• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.59-63
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• 2014

This paper describes the basic principles of 3D broadcast system and proposes new 3D broadcast technology that reduces the amount of data by applying CS(Compressed Sensing). Differences between Sampling theory and the CS technology concept were described. Recently proposed CS algorithm AMP(Approximate Message Passing) and CoSaMP(Compressive Sampling Matched Pursuit) were described. This paper compared an accuracy between two algorithms and a calculation time that image data compressed and restored by these algorithms. As result determines a low complexity algorithm for 3D broadcast system.