• Title/Summary/Keyword: Image Frequency

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Medical Image Enhancement Using an Adaptive Weight and Threshold Values (적응적 가중치와 문턱치를 이용한 의료영상의 화질 향상)

  • Kim, Seung-Jong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.5
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    • pp.205-211
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    • 2012
  • By using an adaptive threshold and weight based on the wavelet transform and Haar transform, a novel image enhancement algorithm is proposed. First, a medical image was decomposed with wavelet transform and all high-frequency sub-images were decomposed with Haar transform. Secondly, noise in the frequency domain was reduced by the proposed soft-threshold method. Thirdly, high-frequency coefficients were enhanced by the proposed weight values in different sub-images. Then, the enhanced image was obtained through the inverse Haar transform and wavelet transform. But the pixel range of the enhanced image is narrower than a normal image. Lastly, the image's histogram was stretched by nonlinear histogram equalization. Experiments showed that the proposed method can be not only enhance an image's details but can also preserve its edge features effectively.

A Visual Quality Enhancement of Medical Image Using Optimized High-Frequency Emphasis Filter (고주파 강조필터를 이용한 의료영상의 화질향상을 위한 최적화 방법)

  • Shin, Choong-Ho;Jung, Chai-Yeoung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.7
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    • pp.1681-1685
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    • 2014
  • The visual quality of medical image is an important factor for diagnosis accuracy. Therefore, the methods to improve the quality of medical image have studied. Among them, frequency domain filter is very powerful method to impove the visual quality of image. In this paper, the X-ray medical image using optimized high-pass filter was improved edges. The result image was improved edge and contrast of flat area using optimized high frequency emphasis filter. At last, the result image is to minimize the noise using the minimum mean square error(MMSE) filter. As a result, the proposed method has enhanced contrast and edge of the image in the contrast of existing filters, with the noise canceling effect.

Digital Image Watermarking using the Wiener Filter (위너 필터를 이용한 디지털 영상 워터마킹)

  • 이시중;김지영;고광식
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.519-522
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    • 2000
  • Digital watermarking has been proposed as a solution to the problem of copyright protection of the multimedia documents. In this paper a new watermarking method for digital images operating in the frequency domain is proposed. In our approach, DCT coefficients of the watermark are added to the low frequency region of the host image, and extract it using the Wiener Filter. Due to the characteristic of the wiener filtering, the watermark is robust to various image processing techniques. Experimental results show that it is possible to reliably extract the watermark without degrading image quality.

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Analog to Digital Converter for CMOS Image Sensor (CMOS Image Sensor에 사용 가능한 아날로그/디지탈 변환)

  • 노주영;윤진한;장철상;손상희
    • Proceedings of the IEEK Conference
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    • 2002.06b
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    • pp.137-140
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    • 2002
  • This paper is proposed a 8-bit anolog to digital converter for CMOS image sensor. A anolog to digital converter for CMOS image sensor is required function to control gain. Proposed anolog to digital converter is used frequency divider to control gain. At 3.3 Volt power supply, total static power dissipation is 8mW and programmable gain control range is 30dB. The gain control range can be easily increased with insertion of additional flip-flop at divided-by-N frequency divider circuit.

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The Selection of the Scenery and Sound as the Environmental Friendly Elements (친환경 요소로서의 경관과 그에 어울리는 소리의 선택)

  • Shin, Yong-Gyu;Jeon, Ji-Hyeon;Jang, Gil-Soo;Kook, Chan
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.11a
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    • pp.682-685
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    • 2005
  • In this research, how the evaluation of the spacial image influenced by the environmental friendly elements included in the visual information, and how the selection of the sound changed depending on the characteristics of spatial image by the 40 subjects were carried out. Vast tracts of green land and the waterfront were highly preferred and impressive than the other spaces. The green music, signal with water sound and bird chirping sound were highly scored. In the frequency characteristics of the factors, the first factor was artificial sound(high at the low frequency band), the second was natural sound(uniform at all frequency band) and the third was water sound(high at the middle and high frequency band over 500Hz). This shows that the proposal of the sound which has the frequency characteristics fit to the spacial image should be selected for the soundscape of the target space.

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Image Data Compression Using Biorthgnal Wavelet Transform and Variable Block Size Edges Extraction (쌍직교 웨이브렛 변환과 가변 블럭 윤곽선 추출에 의한 영상 데이타 압축)

  • 김기옥;김재공
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.7
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    • pp.1203-1212
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    • 1994
  • This paper proposes a variable block size vector quantization based on a biorthogonal wavelet transform for image compression. An image is first decomposed with the biorthogonal wavelet transform into multiresolution image and the wavelet coefficients of the middle frequency bands are segmented using the quadtree sturcture to extract the perceptually important regions in the middle frequency bands. A sedges of middle frequency bands exist the corresponding position of high frequency bands, the complicated quadtree structure of middle frequency bands is equally applied to the high frequency bands. Therefore the overhaed information of the quadtree codes needed to segment the high frequency bands can be reduced. The segmented subblocks are encoded with the codebook designed at the each scales and directions. The simulation results showed that the proposed methods could reproduce higher quality image with bit rate reduced about 20(%) than of the preceding VQ method and sufficiently reduce the bolck effect and the edge degradation.

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SAR Image De-noising Based on Residual Image Fusion and Sparse Representation

  • Ma, Xiaole;Hu, Shaohai;Yang, Dongsheng
    • 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.

A Study on the Design of Image Rejection Interdigital-Filter(IRIF) for 5.8GHz Wireless LAN (5.8GHz 무선 LAN용 영상제거 인터디지털 필터 설계에 관한 연구)

  • 유재문;강정진;안정식
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.3
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    • pp.31-36
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    • 1998
  • In this paper, Image Rejection Interdigital Filter(IRIF) for 5.8GHz wireless LAN was designed and implemented. When the input signal is -30dBm in the 4~8㎓ frequency band, the insertion loss including all kinds of loss is 6.3dB in the center frequency 5.775GHz. Therefore, it was showed practically insertion loss of about -3.3dB. Especially, image signal rejection is about -l7dB in the image frequency 6.475GHz. and skirt characteristics of the high frequency band is very excellent. Therefore, it was confirmed that the proposed IRIF is suitable for RF image signal rejection in the 5.8GHz wireless LAN system.

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Facial Image Segmentation using Wavelet Transform (웨이브렛 변환을 적용한 얼굴영상분할)

  • 김장원;박현숙;김창석
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.37 no.3
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    • pp.45-52
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    • 2000
  • In this study, we propose the image segmentation algorithm for facial region segmentation. The proposed algorithm separates the mean image of low frequency band from the differential image of high frequency band in order to make a boundary using HWT, and then we reduce the isolation pixels, projection pixels, and overlapped boundary pixels from the low frequency band. Also the boundaries are detected and simplified by the proposed boundary detection algorithm, which are cleared on the thinning process of 1 pixel unit. After extracting facial image boundary by using the proposed algorithm, we make the mask and segment facial image through matching original image. In the result of facial region segmentation experiment by using the proposed algorithm, the successive facial segmentation have 95.88% segmentation value.

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An Image Data Compression Algorithm by Means of Separating Edge Image and Non-Edge Image (윤곽선화상과 배경화상을 분리 처리하는 화상데이타 압축기법)

  • 최중한;김해수;조승환;이근영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.2
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    • pp.162-171
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    • 1991
  • This paper presents an algorithm for compressing image data by separating the image into two parts. I.e. edge image containing high-frequency components and non-edge image containing low-frequency components of image. The edge image is extracted by using 8 level compass gradient masks and the non-edge image is obtained by removing the edge image from the original image. The edge image is coded by Huffman run-length code and the non edge image is transformed first by DCT and the transformed images is coded next by a quantized bit allocation table. For an example image. GIRL. the proposed algorithm shows bit rate of 0.52 bpp with PSNR of 36dB.

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