• 대한원격탐사학회지
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• 제36권4호
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• pp.545-555
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• 2020

This paper focuses on automatic image registration between EO (Electro-Optical) and IR (InfraRed) satellite images with different spectral properties using block-based approach and simple preprocessing technique to enhance the performance of feature matching. If unpreprocessed EO and IR images from Kompsat-3A satellite were applied to local feature matching algorithms(Scale Invariant Feature Transform, Speed-Up Robust Feature, etc.), image registration algorithm generally failed because of few detected feature points or mismatched pairs despite of many detected feature points. In this paper, we proposed a new image registration method which improved the performance of feature matching with block-based registration process on 9-divided image and pre-processing technique based on adaptive histogram equalization. The proposed method showed better performance than without our proposed technique on visual inspection and I-RMSE. This study can be used for automatic image registration between various images acquired from different sensors.

• Current Optics and Photonics
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• 제8권3호
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• pp.215-224
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• 2024

In medium- and long-range optical imaging systems, atmospheric turbulence causes blurring and distortion of images, resulting in loss of image information. An image-restoration method based on an adaptive feature-fusion multi-input-multi-output (MIMO) dense U-shaped network (Unet) is proposed, to restore a single image degraded by atmospheric turbulence. The network's model is based on the MIMO-Unet framework and incorporates patch-embedding shallow-convolution modules. These modules help in extracting shallow features of images and facilitate the processing of the multi-input dense encoding modules that follow. The combination of these modules improves the model's ability to analyze and extract features effectively. An asymmetric feature-fusion module is utilized to combine encoded features at varying scales, facilitating the feature reconstruction of the subsequent multi-output decoding modules for restoration of turbulence-degraded images. Based on experimental results, the adaptive feature-fusion MIMO dense U-shaped network outperforms traditional restoration methods, CMFNet network models, and standard MIMO-Unet network models, in terms of image-quality restoration. It effectively minimizes geometric deformation and blurring of images.

• Communications for Statistical Applications and Methods
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• 제19권2호
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• pp.225-235
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• 2012

다양한 이유로 인하여 발생하는 영상 잡음은 영상의 화질을 악화시키므로 발생한 잡음을 제거, 감소하는 것이 영상처리 분야에서 매우 중요한 문제이다. 이러한 문제를 해결하는데 가장 근본적인 어려움은 영상 정보에서 제거해야할 잡음과 보존해야 할 신호를 구별하는 것이 쉽지 않다는 것이다. 단순평활법과 같은 잡음 제거과정은 영상을 개선하는데 사용되는 기초적이고 중요한 방법이지만 영상을 오염시키는 잡음의 크기를 고려하지 않는 결점이 있다. 즉, 이러한 방법을 사용하면 잡음을 감소시키는 효과와 함께 잡음이 적거나 없는 부분까지도 열화되어 영상이 흐릿해지는 단점을 보이게 된다. 본 연구에서는 입력 영상에서 신호와 잡음을 효과적으로 구별하여 잡음의 상대적인 크기에 따라 적응적으로 잡음을 제거할 수 있는 방법을 블록 방법을 이용하여 제안한다. 모의실험 결과, 본 연구에서 제안하는 알고리즘에 의해 적응적으로 잡음을 제거함으로써 전체적인 영상의 질이 개선되는 것을 확인하였다.

• 한국위성정보통신학회논문지
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• 제7권3호
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• pp.116-120
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• 2012

전 세계적으로 빌딩 에너지 세이빙에 대한 관심이 증가하고 있으며, BEMS(Building Energy Management System)을 효율적으로 운용하기 위한 IT 기술에 대한 연구를 지속적으로 진행하고 있다. 최근 LED 조명기술의 발전으로 LED를 제어하여 에너지 절감효과를 극대화 할 수 있으며 BEMS에 이러한 LED 조명 제어기술들이 개발되고 있다. 본 논문에서는 건물에 설치되어 있는 IP 카메라와 Adaptive GMM(Gaussian Mixture Model)을 이용하여 BEMS용 LED 조명제어에 대한 시스템을 제안하였다. 설계한 구조를 기반으로 빌딩의 영상을 실시간으로 모니터링하고, 동적 객체를 영상추적하며, 다수의 객체를 클러스터링하고 인체 이동을 감지하여 LED 조명을 제어하는 기능을 제안하고, 관련 Software 개발을 통해 구현가능성을 입증하였다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2008년도 제39차 동계학술발표논문집 16권2호
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• pp.207-210
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• 2009

Edge detection is an important process in low level image processing. But many proposed methods for edge detection are not very robust to the image noise and are not flexible for different images. To solve the both problems, an algorithm is proposed which eliminate the noise by mean shift algorithm in advance, and then adaptively determine the double thresholds based on gradient histogram and minimum interclass variance, With this algorithm, it can fade out almost all the sensitive noise and calculate the both thresholds for different images without necessity to setup any parameter artificially, and choose edge pixels by fuzzy algorithm.

• 한국생산제조학회지
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• 제20권4호
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• pp.369-375
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• 2011

Design is important in the IT, digital appliance, and auto industries. Aesthetic and art images are being applied for better quality of the products. Most image patterns are complex and much lead-time is required to implement them to the product design process. A precise reverse engineering method generating 2.5D engraving models from 2D artistic images is proposed through the image processing, NURBS interpolation and 2.5D reconstruction methods. To generate 2.5D TechArt models from the art images, boundary points of the images are extracted by using the adaptive median filter and the novel MBF (modified boundary follower) algorithm. Accurate NURBS interpolation of the points generates TechArt CAD models. Performance of the developed system has been confirmed through the quick turnaround 2.5D engraving simulation linked with the commercial CAD/CAM system.

• Journal of Electrical Engineering and information Science
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• 제2권6호
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• pp.36-42
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• 1997

This paper presents a new design technique for performing high quality low bit rate image compression. A hybrid coder(HC) which combines Mean Removed Important Coefficient Selection based JPEG(MR-ICS-JPEG) and Adaptive Vector Quantization (AVQ) is proposed. A new quantization table is developed using the Important Coefficient Selection(ICS) method; the importance of each coefficient is determined using the orthonormal property of the DCT. This quantization table is applied to standard JPEG with mean removal(MR) strategy before processing. This scheme, called MR-ICS-JPEG, produces more than 2 dB enhanced performance in terms of PSNR over standard JPEG. A set of homogeneous codebooks is generated by homogeneous training vectors. Before compression, an image is uniformly divided into 8${\times}$8 blocks. Low detail regions such as backgrounds are roughly coded by AVQ while high detail regions such as edges or curves are finely coded by the proposed MR-ICS-JPEG. This hybrid coder procuces consistently about 3 dB improved performance in terms of PSNR over standard JPEG.

• 전자공학회논문지S
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• 제34S권8호
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• pp.92-103
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• 1997

This paper proposes a new gray-level image segmentation method using GA(genetic algorithm) and an ACA(adaptive clustering algorithm). The solution in the general GA can be moving because of stochastic reinsertion, and suffer from the premature convergence problem owing to deficiency of individuals before finding the optimal solution. To cope with these problems and to reduce processing time, we propose the new GBR algorithm and the technique that resolves the premature convergence problem. GBR selects the individual in the child pool that has the fitness value superior to that of the individual in the parents pool. We resolvethe premature convergence problem with producing the mutation in the parents population, and propose the new method that removes the small regions in the segmented results. The experimental results show that the proposed segmentation algorithm gives better perfodrmance than the ACA ones in Gaussian noise environments.

• JSTS:Journal of Semiconductor Technology and Science
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• 제13권1호
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• pp.34-42
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• 2013

Human faces have been broadly studied in digital image and video processing fields. An appearance-based method, the adaptive boosting learning algorithm using integral image representations has been successfully employed for face detection, taking advantage of the feature extraction's low computational complexity. In this paper, we propose a face-detection postprocessing method that equalizes instantaneous facial regions in an efficient hardware architecture for use in real-time multimedia applications. The proposed system requires low hardware resources and exhibits robust performance in terms of the movements, zooming, and classification of faces. A series of experimental results obtained using video sequences collected under dynamic conditions are discussed.

• 한국산업정보학회논문지
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• 제12권3호
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• pp.132-140
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• 2007

카메라 영상은 명도의 변화와 부정확한 초점으로 인해 스캐너 영상에 비하여 화질이 저하된다. 본 연구에서는 카메라 영상에서 자주 발생하는 화질 저하에 대한 적응력을 강화하여 카메라기반 문서 인식에 적합한 이진화 방법을 제안한다. 기존의 평가에서 우수하다고 보고된 이진화 방법을 기반으로 하되, 낮은 조도와 부정확한 초점으로 인해 명도 대비가 낮은 영상에 대한 적응력을 강화하였다. 또한 이진화 시 국소 윈도우를 이용하여 기존의 방법에서 뭉개지기 쉬운 문자의 세부 구조를 섬세하게 추출하도록 개선하였다. 실험에서는 기존에 우수하다고 평가된 이진화 방법들과 제안하는 방법을 문서 인식에 적용하여 다양한 카메라 문서 영상에 대한 성능을 비교하였는데, 그 결과 제안하는 방법이 카메라로 입력받은 문서 영상의 인식에 효과적임을 확인하였다.