• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.679-686
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• 2014

Recently, users can get countless images and videos by network. So, the compression technology of image and video is researched more and more. However, the situation which is the interested range of the image is occurred. For instance, since the region of face is more important than background, the image compression technology bases on the region of interest (ROI) is necessary, in the ATM environment. In this research, given the human visual system, which are not sensitive to illumination variations at very dark and light regions of image, we calculate the standard deviation of block and use this value to define the ROI. In encoding process, the relatively high quality can be obtained at the ROI and the relatively low quality can be obtained at the non ROI. In proposed scheme, the feature which is the encoding process according to subjectively image quality can be demonstrated. Finally, this proposed scheme is applied to JPEG standard. The experimental results demonstrate that proposed scheme can achieve better image quality at the high compression ratio.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.257-266
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• 2020

It is very important to share tactical information such as video, images, and text messages among soldiers for situational awareness. Under the wireless environment of the battlefield, the available bandwidth varies dynamically and is insufficient to transmit high quality images, so it is necessary to minimize the distortion of the area of interests such as targets. A natural operating method for soldiers is also required considering the difficulty in handling while moving. In this paper, we propose a natural ROI(region of interest) setting and image compression method for effective image sharing among soldiers. We verify the proposed method through prototype system design and implementation of eye gaze detection and ROI-based image compression.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.40-56
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• 2017

Since the progress of digital medical imaging techniques, it has been needed to compress the variety of medical images. In medical imaging, reversible compression of image's region of interest (ROI) which is diagnostically relevant is considered essential. Then, improving the global compression rate of the image can also be obtained by separately coding the ROI part and the remaining image (called background). For this purpose, the present work proposes an efficient reversible discrete cosine transform (RDCT) based embedded image coder designed for lossless ROI coding in very high compression ratio. Motivated by the wavelet structure of DCT, the proposed rearranged structure is well coupled with a lossless embedded zerotree wavelet coder (LEZW), while the background is highly compressed using the set partitioning in hierarchical trees (SPIHT) technique. Results coding shows that the performance of the proposed new coder is much superior to that of various state-of-art still image compression methods.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.275-302
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• 2007

We propose a novel still image compression system which supports a high quality text compression function. The system segments the text from the image and compresses the text with a high quality. The system shows 48:1 high compression ratio using context-based adaptive binary arithmetic coding. The arithmetic coding performs the high compression by the codeblocks in the bitplane. The input of the system consists of a segmentation mode and a ROI(Region Of Interest) mode. In segmentation mode, the input image is segmented into a foreground consisting of text and a background consisting of the remaining region. In ROI mode, the input image is represented by the region of interest window. The high quality text compression function with a high compression ratio shows that the proposed system can be comparable with the JPEG2000 products. This system also uses gray coding to improve the compression ratio.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.853-856
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• 2004

Image data processing on the region of interest (ROI) for providing the primary information is needed the view of saving search time and bandwidth over image communications related to web browsing, image database, and telemedicine, etc. Hence, the issue on extracting the region of interest is drawing a plenty of attention for the communication environment with a relatively low bandwidth such as mobile internet. In this paper, we propose a improved standard Maxshift method. The proposed algorithm compress image that includes multiple ROI using Maxshift method in Part 1 of JPEG2000. Simulation results show that proposed method increases PSNR vs. compression ratio performance above the Maxshift method.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.411-420
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• 2004

We propose a novel still image compression system, which is superior in its function than the JPEG2000 system developed by David Taubman. The system shows 40 : 1 high compression ratio using $2\times2$ bitmatrix subblock coding. The $2\times2$ bitmatrix subblock is constructed in the bitplanes by organizing the bits into subblocks composing of $2\times2$matrices. The arithmetic coding performs the high compression by the bitmatrices in the subblock. The input of the system consists of a segmentation mode and a ROI(Region Of Interest) mode. In segmentation mode, the input image is segmented into a foreground consisting of letters and a background consisting of the remaining region. In ROI mode, the input image is represented by the region of interest window. The high compression ratio shows that the proposed system is competent among the JPEG2000 products currently in the market. This system also uses gray coding to improve the compression ratio.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.324-332
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• 2004

In image communications related to web browsing, image database, and telemedicine, image data processing on the region of interest (ROI) for providing the primary information is needed in the view of saying search time and bandwidth. In this paper, an enhanced algorithm for processing image data that involves multiple ROIs is presented in order to increase PSNR vs. compression ratio performance above the previous JPEG2000 Part1 Maxshift method. Since the wavelet transform enables us to a progressive transmission mechanism, Multiple-ROI coding is possible to compress, transmit, and reconstruct the image data with a better quality than those of non-ROI method while the required transmission bandwidth is kept relatively low.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1445-1454
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• 2006

To compress a specific part of an image with high quality or to transfer it, JPEG2000 standard offers an ROI(Region-of-Interest) image coding method. What is important in ROI coding is to process relative importance between ROI and background and to process ROI mask. We propose an adaptive ROI coding method supplemented the existing Implicit ROI coding and Modified implicit ROI coding to improve image quality and reduce ROI mask information. The proposed method is an EBCOT-based ROI coding that extracts ROI from the compressed bitstream, and gets the ROI mask information by classifying the codeblocks into 6 patterns. The information includes the pattern type(3bit) and the width(5bit) expressing the boundary between two regions for each codeblock. As a result, the method shows an excellent compression performance in ROI region as well as in the whole region of an image.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.601-615
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• 2015

Region of interest (ROI) is the most informative part of a medical image and mostly has been used as a major part of watermark. Various shapes ROIs selection have been reported in region-based watermarking techniques. In region-based watermarking schemes an image region of non-interest (RONI) is the second important part of the image and is used mostly for watermark encapsulation. In online healthcare systems the ROI wrong selection by missing some important portions of the image to be part of ROI can create problem at the destination. This paper discusses the complete medical image availability in original at destination using the whole image as a watermark for authentication, tamper localization and lossless recovery (WITALLOR). The WITALLOR watermarking scheme ensures the complete image security without of ROI selection at the source point as compared to the other region-based watermarking techniques. The complete image is compressed using the Lempel-Ziv-Welch (LZW) lossless compression technique to get the watermark in reduced number of bits. Bits reduction occurs to a number that can be completely encapsulated into image. The watermark is randomly encapsulated at the least significant bits (LSBs) of the image without caring of the ROI and RONI to keep the image perceptual degradation negligible. After communication, the watermark is retrieved, decompressed and used for authentication of the whole image, tamper detection, localization and lossless recovery. WITALLOR scheme is capable of any number of tampers detection and recovery at any part of the image. The complete authentic image gives the opportunity to conduct an image based analysis of medical problem without restriction to a fixed ROI.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.143-152
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• 2006

JPEG2000, the standard of still image compression based on wavelet, will be widely used. One of the greatest characteristics of JPEG2000 is to offer ROI(Region-Of-Interest) coding. This is to compress with high quality the region that the user wants better than the other region. JPEG2000 and ROI have different parameters, which are tile size and ROI size, wavelet filter type and ROI shape and its location, codeblock size and number of ROI, number of DWT decomposition level and ROI importance, and number of quality layer and low resolution sub-band importance. In this paper, we shows the correlation of the parameters and ROI coding methods through experiments. This helps an application select the parameters and the methods to meet the application.