• Title/Summary/Keyword: Adaptive Image Processing

Search Result 452, Processing Time 0.027 seconds

Automatic Estimation of Spatially Varying Focal Length for Correcting Distortion in Fisheye Lens Images

  • Kim, Hyungtae;Kim, Daehee;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
    • /
    • v.2 no.6
    • /
    • pp.339-344
    • /
    • 2013
  • This paper presents an automatic focal length estimation method to correct the fisheye lens distortion in a spatially adaptive manner. The proposed method estimates the focal length of the fisheye lens by generating two reference focal lengths. The distorted fisheye lens image is finally corrected using the orthographic projection model. The experimental results showed that the proposed focal length estimation method is more accurate than existing methods in terms of the loss rate.

  • PDF

A Modified Steering Kernel Filter for AWGN Removal based on Kernel Similarity

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of information and communication convergence engineering
    • /
    • v.20 no.3
    • /
    • pp.195-203
    • /
    • 2022
  • Noise generated during image acquisition and transmission can negatively impact the results of image processing applications, and noise removal is typically a part of image preprocessing. Denoising techniques combined with nonlocal techniques have received significant attention in recent years, owing to the development of sophisticated hardware and image processing algorithms, much attention has been paid to; however, this approach is relatively poor for edge preservation of fine image details. To address this limitation, the current study combined a steering kernel technique with adaptive masks that can adjust the size according to the noise intensity of an image. The algorithm sets the steering weight based on a similarity comparison, allowing it to respond to edge components more effectively. The proposed algorithm was compared with existing denoising algorithms using quantitative evaluation and enlarged images. The proposed algorithm exhibited good general denoising performance and better performance in edge area processing than existing non-local techniques.

AN INTERFERENCE FRINGE REMOVAL METHOD BASED ON MULTI-SCALE DECOMPOSITION AND ADAPTIVE PARTITIONING FOR NVST IMAGES

  • Li, Yongchun;Zheng, Sheng;Huang, Yao;Liu, Dejian
    • Journal of The Korean Astronomical Society
    • /
    • v.52 no.2
    • /
    • pp.49-55
    • /
    • 2019
  • The New Vacuum Solar Telescope (NVST) is the largest solar telescope in China. When using CCDs for imaging, equal-thickness fringes caused by thin-film interference can occur. Such fringes reduce the quality of NVST data but cannot be removed using standard flat fielding. In this paper, a correction method based on multi-scale decomposition and adaptive partitioning is proposed. The original image is decomposed into several sub-scales by multi-scale decomposition. The region containing fringes is found and divided by an adaptive partitioning method. The interference fringes are then filtered by a frequency-domain Gaussian filter on every partitioned image. Our analysis shows that this method can effectively remove the interference fringes from a solar image while preserving useful information.

A Study on Modified Adaptive Median Filter for Impulse Noise Removal (임펄스 잡음 제거를 위한 변형된 적응 메디안 필터에 관한 연구)

  • Long, Xu;An, Young-Joo;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2014.05a
    • /
    • pp.804-806
    • /
    • 2014
  • During the transmission process of processing of image, various noises are added causing an error to the image. In order to restore these images, methods such as alpha trimmed average filter, standard median filter and switching median filter were proposed but such previous methods has insufficient noise suppression characteristics. Therefore in this paper, in order to remove the impulse noise added to the image, an adaptive median filter algorithm modified to expand the mask according to the noise density of mask pixels was proposed.

  • PDF

An Adaptive Binarization of Camera Document Image by Image Quality Estimation (화질 분석을 통한 카메라 문서 영상의 적응적 이진화)

  • Kim, In-Jung
    • Journal of KIISE:Software and Applications
    • /
    • v.34 no.9
    • /
    • pp.797-803
    • /
    • 2007
  • Adaptive binarization is very important for the camera-based document recognition. This paper proposes a binarization method which can effectively adapt to the variation of image Qualify. Firstly, it analyzes the effect of binarization parameters to the result and proposes a method to measure the image quality. Then, it statistically analyzes the relationship between the image quality and the binarization parameter. Finally, it proposes a binarization method that automatically adapts to the quality of the input image, using the analysis result. The experiment results show that there is a meaningful relationship between the image quality and the binarization parameter, and therefore, the proposed method can effectively adapt to the variation of image quality.

An Image Contrast Enhancement Technique Using Integrated Adaptive Fuzzy Clustering Model (IAFC 모델을 이용한 영상 대비 향상 기법)

  • 이금분;김용수
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2001.12a
    • /
    • pp.279-282
    • /
    • 2001
  • This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) Model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved MEC can classify the image into two classes with unsupervised teaming rule. The proposed method is applied to some experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

  • PDF

Design of Unsharp Mask Filter based on Retinex Theory for Image Enhancement

  • Kim, Ju-young;Kim, Jin-heon
    • Journal of Multimedia Information System
    • /
    • v.4 no.2
    • /
    • pp.65-73
    • /
    • 2017
  • This paper proposes a method to improve the image quality by designing Unsharp Mask Filter (UMF) based on Retinex theory which controls the frequency pass characteristics adaptively. Conventional unsharp masking technique uses blurring image to emphasize sharpness of image. Unsharp Masking(UM) adjusts the original image and sigma to obtain a high frequency component to be emphasized by the difference between the blurred image and the high frequency component to the original image, thereby improving the contrast ratio of the image. In this paper, we design a Unsharp Mask Filter(UMF) that can process the contrast ratio improvement method of Unsharp Masking(UM) technique with one filtering. We adaptively process the contrast ratio improvement using Unsharp Mask Filter(UMF). We propose a method based on Retinex theory for adaptive processing. For adaptive filtering, we control the weights of Unsharp Mask Filter(UMF) based on the human visual system and output more effective results.

Post-filtering in Low Bit Rate Moving Picture Coding, and Subjective and Objective Evaluation of Post-filtering (저 전송률 동화상 압축에서 후처리 방법 및 후처리 방법의 주관적 객관적 평가)

  • 이영렬;김윤수;박현욱
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.24 no.8B
    • /
    • pp.1518-1531
    • /
    • 1999
  • The reconstructed images from highly compressed MPEG or H.263 data have noticeable image degradations, such as blocking artifacts near the block boundaries, corner outliers at cross points of blocks, and ringing noise near image edges, because the MPEG or H.263 quantizes the transformed coefficients of 8$\times$8 pixel blocks. A post-processing algorithm has been proposed by authors to reduce quantization effects, such as blocking artifacts, corner outliers, and ringing noise, in MPEG-decompressed images. Our signal-adaptive post-processing algorithm reduces the quantization effects adaptively by using both spatial frequency and temporal information extracted from the compressed data. The blocking artifacts are reduced by one-dimensional (1-D) horizontal and vertical low pass filtering (LPF), and the ringing noise is reduced by two-dimensional (2-D) signal-adaptive filtering (SAF). A comparison study of the subjective quality evaluation using modified single stimulus method (MSSM), the objective quality evaluation (PSNR) and the computation complexity analysis between the signal-adaptive post-processing algorithm and the MPEG-4 VM (Verification Model) post-processing algorithm is performed by computer simulation with several MPEG-4 image sequences. According to the comparison study, the subjective image qualities of both algorithms are similar, whereas the PSNR and the comparison complexity analysis of the signal-adaptive post-processing algorithm shows better performance than the VM post-processing algorithm.

  • PDF

Adaptive thresholding for two-dimensional barcode images using two thresholds and the integral image (이중 문턱 값과 적분영상을 이용한 2차원 바코드 영상의 적응적 이진화)

  • Lee, Yeon-Kyung;Yoo, Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.16 no.11
    • /
    • pp.2453-2458
    • /
    • 2012
  • In this paper, we propose an adaptive thresholding method to binarize two-dimensional barcode images. Adaptive thresholding methods that minimize light effects convert an original image into a binary image. The methods are applied to document image binarization. The methods, however, have problems of determining box size used in adaptive thresholding. thus, they inappropriate to use in recognition of two-dimensional barcode images. To overcome the problem, we analysis the problem and propose a new adaptive threshold method using the integral image. To show the effectiveness of our method, we compared our method with the well-known existing methods in terms of visual quality and processing time. The experimental result indicates that the proposed method is superior to the existing method.

Image Enhancement Using Adaptive Weighted Sigma Filter (적응비중화 시그마필터에 의한 영상향상)

  • Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
    • /
    • v.44 no.2 s.314
    • /
    • pp.19-26
    • /
    • 2007
  • In the sigma filter, there is a specialized neighbours distribution scheme in which the sigma value is computed from local statistics. It is designed to modify a standard average filter to preserve edges. However this filter is vulnerable to details-enhancement and conventional sigma approaches have been focused on denoising, not enhancing the characteristic area. This paper proposes an adaptive image enhancement algorithm using local statistics and functional synthesis which are utilized for adaptive realization of the enhancement, so that not only image noise may be smoothed but also details may be enhanced. For the local adaptation, parameters are estimated and weighted at each moving window that satisfy the criteria. The experimental results illuminates the effectiveness of the proposed method.