• Title/Summary/Keyword: Space Images

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A Study on Hair Styles Featuring Technological Images (테크놀로지 이미지적 헤어스타일에 관한 연구)

  • Oh, Moon-Gyun;Im, Young-Ja
    • Journal of the Korean Society of Fashion and Beauty
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    • v.2 no.1 s.1
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    • pp.34-45
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    • 2004
  • Hair styles which independently coexist by transcending the time and space under the environment of highly developed information and communication technology of recent years, were analyzed. Moreover the concerned trends of art which influenced on these styles were introduced in this study. Through IT based information exchange produced new hair styles which have the technological images. The characteristics of these hair styles are investigated also. For the examination of yearly trends, hair styles in fashion collections of Yves Saint Larent during 1962 to 1999 were examined and classified. The results show that time variated trends are appeared in this period. For the analysis of the trends of hair styles featuring technological images, hair styles in fashion collection of Christian Dior, Giorgio Armani, Gucci, Jean Paul Gaultier and Chanel in the early 2000s are quoted.

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Hue Preserved Multi-scale Retinex to Improve Color Reproduction

  • Kyung, Wang-Jun;Lee, Tae-Hyung;Lee, Cheol-Hee;Ha, Yeong-Ho
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.1546-1549
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    • 2009
  • In recent studies on tone reproduction with the objective of reproducing natural looking colors in digital images, an integrated multi-scale retinex (IMSR) has produced great naturalness in the resulting images. Most methods, including IMSR, work in RGB or quasi-RGB color spaces. As such, this produces hue distortion from the perspective of the human visual system. Accordingly, this paper proposes the hue preserved multi-scale Retinex (HPMSR) method to obtain a high contrast and naturalness. The proposed method enhanced the $L^*$ and saturation values in CIELAB color space. As a result, the visibility in dark shadows in the resulting images was improved.

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Simple Application Cases of Morphing Method using Geo-spatial Data

  • Lee, Ki-Won;Park, Yong-Jae
    • Korean Journal of Remote Sensing
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    • v.24 no.3
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    • pp.251-256
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    • 2008
  • Morphing method, one of classic image processing algorithms, has been used in various application fields. The motivation of this work is to investigate its applicability in consideration to geo-spatial data including airborne or space-borne images. For this purpose, the Beier and Neely morphing algorithm is tentatively implemented in the form of a prototype with user interface. As the results, this feature-based morphing with paired image sets can be used for general users: image simulation using two or more images and construction of color-blending image between source image and destination image in different types. Some simple application cases were demonstrated. This scheme is the simple and useful approach for those who want to utilize both geo-spatial data sets and airborne/space-borne image sets.

Lab Color Space based Rice Yield Prediction using Low Altitude UAV Field Image

  • Reza, Md Nasim;Na, Inseop;Baek, Sunwook;Lee, In;Lee, Kyeonghwan
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2017.04a
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    • pp.42-42
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    • 2017
  • Prediction of rice yield during a growing season would be very helpful to magnify rice yield as it also allows better farm practices to maximize yield with greater profit and lesser costs. UAV imagery based automatic detection of rice can be a relevant solution for early prediction of yield. So, we propose an image processing technique to predict rice yield using low altitude UAV images. We proposed $L^*a^*b^*$ color space based image segmentation algorithm. All images were captured using UAV mounted RGB camera. The proposed algorithm was developed to find out rice grain area from the image background. We took RGB image and applied filter to remove noise and converted RGB image to $L^*a^*b^*$ color space. All color information contain in both $a^*$ and $b^*$ layers and by using k-mean clustering classification of these colors were executed. Variation between two colors can be measured and labelling of pixels was completed by cluster index. Image was finally segmented using color. The proposed method showed that rice grain could be segmented and we can recognize rice grains from the UAV images. We can analyze grain areas and by estimating area and volume we could predict rice yield.

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Measurement Coding for Compressive Sensing of Color Images

  • Dinh, Khanh Quoc;Trinh, Chien Van;Nguyen, Viet Anh;Park, Younghyeon;Jeon, Byeungwoo
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.1
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    • pp.10-18
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    • 2014
  • From the perspective of reducing the sampling cost of color images at high resolution, block-based compressive sensing (CS) has attracted considerable attention as a promising alternative to conventional Nyquist/Shannon sampling. On the other hand, for storing/transmitting applications, CS requires a very efficient way of representing the measurement data in terms of data volume. This paper addresses this problem by developing a measurement-coding method with the proposed customized Huffman coding. In addition, by noting the difference in visual importance between the luma and chroma channels, this paper proposes measurement coding in YCbCr space rather than in conventional RGB color space for better rate allocation. Furthermore, as the proper use of the image property in pursuing smoothness improves the CS recovery, this paper proposes the integration of a low pass filter to the CS recovery of color images, which is the block-based ${\ell}_{20}$-norm minimization. The proposed coding scheme shows considerable gain compared to conventional measurement coding.

Regional Variations in Spectra of (25143) Itokawa taken with Hayabusa/AMICA

  • Jin, Sunho;Ishiguro, Masateru
    • The Bulletin of The Korean Astronomical Society
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    • v.43 no.1
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    • pp.73.2-73.2
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    • 2018
  • The Hayabusa remote-sensing images of near-Earth asteroid (25143) Itokawa exhibited large diversity in spectral properties. The evidence suggests a various degrees of space weathering on the surface. It is known that the space weathering changes the spectra of S-type asteroids redder and reduces the depths of absorption around $1{\mu}m$. It is therefore possible to determine the surface ages through the investigation of the degree of space weathering. It is, however, reported that the scattered light components severely degrade the Asteroid Multiband Imaging Camera (AMICA) images, especially at the wavelengths > $0.86{\mu}m$. Our team came up with a technique for subtracting the scattered light components (Ishiguro 2014). Here, we upgraded the techniqu e by applying simplex algorism to correct the artifacts for all AMICA bands. This new technique enables to apply for the longest channel (i.e., zs-band at $1.01{\mu}m$) images, which was not studied so far. With the AMICA all bands data, we estimated the surface ages at the different location to be 0.6-2 Myr. Based on this data together with the geological information (e.g. gravitational potentials and local). we will discuss about the evolution of surface materials on the asteroid.

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A Study on Production of Optimum Profile Considered Color Rendering in Input Device (입력 장치에서 컬러 랜더링을 고려한 최적의 프로파일 제작에 관한 연구)

  • Koo, Chul-Whoi;Cho, Ga-Ram;Lee, Sung-Hyung
    • Journal of the Korean Graphic Arts Communication Society
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    • v.28 no.2
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    • pp.117-128
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    • 2010
  • Advancements in digital image have put high quality digital camera into the hands of many image professionals and consumers alike. High quality digital camera images consist originally of raw which have a set of color rendering operation applied to them to produce good images. With color rendering, the raw file was converted to Adobe RGB and sRGB color space. Also color rendering can incorporate factor such as white balance, contrast, saturation. Therefore, in this paper we conduct a study on production of optimum profile considered color rendering in digital camera. To do the experiment, the images were Digital ColorChecker SG target and ColorChecker DC target. A profiling tool was ProfileMaker 5.03. The results were analyzed by comparing in color gamut of $CIEL^*a^*b^*$ color space and calculating ${\Delta}E^*_{ab}$. Also results were analyzed in terms of different $CIEL^*a^*b^*$ color space quadrants based on lightness, chroma.

Denoising Diffusion Null-space Model and Colorization based Image Compression

  • Indra Imanuel;Dae-Ki Kang;Suk-Ho Lee
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.2
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    • pp.22-30
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    • 2024
  • Image compression-decompression methods have become increasingly crucial in modern times, facilitating the transfer of high-quality images while minimizing file size and internet traffic. Historically, early image compression relied on rudimentary codecs, aiming to compress and decompress data with minimal loss of image quality. Recently, a novel compression framework leveraging colorization techniques has emerged. These methods, originally developed for infusing grayscale images with color, have found application in image compression, leading to colorization-based coding. Within this framework, the encoder plays a crucial role in automatically extracting representative pixels-referred to as color seeds-and transmitting them to the decoder. The decoder, utilizing colorization methods, reconstructs color information for the remaining pixels based on the transmitted data. In this paper, we propose a novel approach to image compression, wherein we decompose the compression task into grayscale image compression and colorization tasks. Unlike conventional colorization-based coding, our method focuses on the colorization process rather than the extraction of color seeds. Moreover, we employ the Denoising Diffusion Null-Space Model (DDNM) for colorization, ensuring high-quality color restoration and contributing to superior compression rates. Experimental results demonstrate that our method achieves higher-quality decompressed images compared to standard JPEG and JPEG2000 compression schemes, particularly in high compression rate scenarios.

Day and night license plate detection using tail-light color and image features of license plate in driving road images

  • Kim, Lok-Young;Choi, Yeong-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.7
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    • pp.25-32
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    • 2015
  • In this paper, we propose a license plate detection method of running cars in various road images. The proposed method first classifies the road image into day and night images to improve detection accuracy, and then the tail-light regions are detected by finding red color areas in RGB color space. The candidate regions of the license plate areas are detected by using symmetrical property, size, width and variance of the tail-light regions, and to find the license plate areas of the various sizes the morphological operations with adaptive size structuring elements are applied. Finally, the plate area is verified and confirmed with the geometrical and image features of the license plate areas. The proposed method was tested with the various road images and the detection rates (precisions) of 84.2% of day images and 87.4% of night images were achieved.

Using Kalman Filtering and Segmentation Techniques to Capture and Detect Cracks in Pavement

  • Hsu, C.J.;Chen, C.F.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.930-932
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    • 2003
  • For this study we used a CCD video camera to capture the pavement image information via the computer. During investigation processing, the CCD video camera captured 10${\sim}$30 images per second. If the vehicle velocity is too fast, the collected images will be duplicated and if the velocity is too slow there will be a gapped between images. Therefore, in order to control the efficiency of the image grabber we should add accessory tools such as the Differential Global Positioning System (DGPS) and odometer. Furthermore, Kalman Filtering can also solve these problems. After the CCD video camera captured the pavement images, we used the Least-Squares method to eliminate images of gradation which have non-uniform surfaces due to the illumination at night. The Fuzzy Entropy method calculates images of threshold segments and creates binary images. Finally, the Object Labeling algorithm finds objects that are cracks or noises from the binary image based on volume pixels of the object. We used these algorithms and tested them, also providing some discussion and suggestions.

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