• 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 the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.197-206
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• 2006

One of the most significant characteristics of JPEG2000. the emerging still image standards. is the ROI (Region of Interest) coding. JPEG2000 provides a number of ROI coding mechanisms and ROI parameters. To apply them to an application, it must select the applicable values. In this paper, we evaluate how the ROI coding mechanisms and the ROI parameters influencing JPEG2000 qualify affect the ROI quality and the whole image quality. The ROI coding mechanisms are Maxshift and Implicit. and the parameters are tile size and ROI size, codeblock size, number of DWT decomposition levels and ROI importance. The bigger the tile size, the better the quality. The bigger the ROI size, the ROI importance and the number of DWT decomposition levels, the worse the qualify. In code block $32{\times}32$ of Maxshift and Implicit, it has the best qualify.

• Journal of Digital Contents Society
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• v.16 no.4
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• pp.583-593
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• 2015

Today, caused by the growth of computer and communication technology, multimedia, especially image data are being used in different application divisions. JPEG2000 that is widely used these days provides a Region-of-Interest(ROI) technique. The extraction of ROI has to be rapidly executed and automatically extracted in a huge amount of image because of being seen preferentially to the users. For this purpose, this paper proposes a method about preferential processing and automatic extraction of ROI using the distribution of edge in the code block of JPEG2000. The steps are the extracting edges, automatical extracting of a practical ROI, grouping the ROI using the ROI blocks, generating the mask blocks and then quantization, ROI coding which is the preferential processing, and EBCOT. In this paper, to show usefulness of the method, we experiment its performance using other methods, and executes the quality evaluation with PSNR between the images not coding an ROI and coding it.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.127-136
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• 2008

A digitized image passes by encoding, storing or transmitting to show it to users. In this process, may be users would want to see a specific region of the image. And depending on the system features or in the case that the resolution of the image is large, it will take a huge time that the image show to the users. In this time, it will be resonable that the part users want to see shows earlier and afterward the other parts show. For this, JPEG2000 standards provide ROI. Although ROI extraction that users specify ROI arbitrarily is the best, people not always participate in doing all the images. There needs an automatic ROI extracting and storing in some images. JPEG2000 should extract and send an ROI automatically when the images is encoded without ROI. This study proposes a method that automatically extracts an ROI, makes the ROI masks, transfers the masked image preferentially and the background. And the study compares and experiments the proposed method and the method not having 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.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.73-77
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• 2010

Purpose: The nuclear medicine technology has been changed. The hard ware is developed so much. Also the soft ware performs a meritorious deed for the development of nuclear medicine technology. We could use the automated region of interest (ROI) instead of manual ROI. We want to know that what difference of quantitative analysis is there between automated ROI and manual ROI Materials and Methods: There are three experimental to make results. The first is what comparing the renal automated ROI and manual ROI. The second is that we compared three threshold ROI that size is difference each others with visible decision. The third is that we compared full, half, quarter automated background, and survey relative function. Results: Although the first has statistically not significant difference, the second and third have significant difference. Threshold, setting smaller threshold then renal outline or bigger, has statistically significant difference (p<0.01). The third is performed with the first experimental. Full background has significant difference, comparing each three type background (p<0.05). Conclusion: The results that there is not significant difference between automated ROI and manual ROI will increase objectivity and operator's convenience. We could know that smaller threshold then renal out line has significant difference in the second experimental. And the third experimental has results because of a increased background nearby live and spleen.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.301-308
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• 2006

Currently, the preferred processing of a user-centered ROI(Region-of-Interest) or a specific region of image than the transmission and decompression of a full image is needed in different applications. This preferred processing has been actively studied about from the ROI coding methods in JPEG2000 standards to the new methods complementing them. But, there does not exist an ROI coding method suitable for all applications. Therefore, this study shows a criterion of selection according to the application requirements for applying an adequate ROI coding method in JPEG2000 applications, and shows the experimental results deciding efficient parameters in the selected methods.

• 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 the Korea Society of Computer and Information
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• v.14 no.1
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• pp.81-89
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• 2009

To support dynamic Region-of-Interest(ROI) in JPEG2000, a fast ROI mask generation is needed. In the existing methods of ROI coding, after scanning all the pixels in order and discriminating ROI, an ROI mask has been generated. Our method scans 4 pixels of the corners in one code block, and then based on those informations, scans the edges from the corners to get the boundaries of ROI and background. These informations are consisted of a distributed information of ROI and two coordinates of the pixels, which are the points the edges and the boundaries meet. These informations are transmitted to encoder and supported for fast ROI mask generation. There were no great differences between the proposed method and the existing methods in quality, but the proposed method showed superiority in speed.

• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.2
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• pp.25-30
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• 2013

Purpose: To evaluate kidney function, renal relative uptake is very important and is affected by kidney and the setting of background region of interest (ROI). In particular, in the case of patients with hydronephrosis to the naked eyes, such as size, position and shape etc. can be difficult to identify. So according to ROI to be set by user, the results are many differences. This study assumes the ROI of a constant kidney. According to the change of background ROI by analyzing renal relative uptake affect how the results are intended to study. Materials and Methods: From January 2012 to February 2013, we analyzed 27 patients with hydronephrosis who were examined MAG3 test in nuclear medicine department of Samsung medical center. After patients were received intravenous injection of $^{99m}Tc-MAG3$ 185 MBq (5 mCi) data were obtained. While we reconstructed images of patients, we've changed background ROI in the process of setting up ROI. First, in the process of renal processing, automatic ROI which set automatically and background ROI which needed to set manually were compared. Second, we set the ROI position separated by above, lateral and bottom of kidney. Third, background setting time were compared with 1-2 min and 2-3 min. Results: The relative uptake occurred in 3.7%p of the errors on average in Automatic & Manual ROI study. And comparison of background ROI position study, located in the lower position was more accurate results. Above, lateral, bottom each of the values 74.6%, 67.6% and 62.0% showed respectively. The standard value was 59.9%. finally, split function range test doesn't show significant difference. Conclusion: The study shows that relative uptake of kidney is affected in the background ROI. Therefore, it should be set by considering various dependent factors.