• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.39-47
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• 2023

This study compares various transformation techniques for multifocus image fusion. Multi-focus image fusion is a procedure of merging multiple images captured at unalike focus distances to produce a single composite image with improved sharpness and clarity. In this research, the purpose is to compare different popular frequency domain approaches for multi-focus image fusion, such as Discrete Wavelet Transforms (DWT), Stationary Wavelet Transforms (SWT), DCT-based Laplacian Pyramid (DCT-LP), Discrete Cosine Harmonic Wavelet Transform (DC-HWT), and Dual-Tree Complex Wavelet Transform (DT-CWT). The objective is to increase the understanding of these transformation techniques and how they can be utilized in conjunction with one another. The analysis will evaluate the 10 most crucial parameters and highlight the unique features of each method. The results will help determine which transformation technique is the best for multi-focus image fusion applications. Based on the visual and statistical analysis, it is suggested that the DCT-LP is the most appropriate technique, but the results also provide valuable insights into choosing the right approach.

• 한국축산시설환경학회지
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• 제5권2호
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• pp.93-100
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• 1999

Pig's original image data was transformed to a binary image, an image excluding head and tail portion from the whole binary image, and a projected image associated with pig's height. Then the length of body, width of shoulder, and area of pig were calculated and the relationships among the above characteristics and pig's weight were analyzed. The results obtained from this study were as follows: 1. Whole binary image data was considered to be improper to determine the pig's weight because the movement of pig's head and tail portion affected the image data. 2. Binary image data excluding head and tail portion from the whole binary image showed a better estimation of the pig's weight than the whole binary image. 3. Pig's should width was analyzed to be improper factor to determine the pig's weight. 4. The projected image associated with pig's height showed the highest correlation between the pig's area of the image and pig's weight(R2=0.9965). From this research the projected image associated with pig's height, which is excluding head and tail portion from the whole body of pig's image, was considered to be the prime factor to measure the pig's weight by the noncontact measurement.

• Journal of Computing Science and Engineering
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• 제4권4호
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• pp.368-387
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• 2010

We propose a novel method for the registration of 3D CT scans to 2D endoscopic images during the image-guided medialization laryngoplasty. This study aims to allow the surgeon to find the precise configuration of the implant and place it into the desired location by employing accurate registration methods of the 3D CT data to intra-operative patient and interactive visualization tools for the registered images. In this study, the proposed registration methods enable the surgeon to compare the outcome of the procedure to the pre-planned shape by matching the vocal folds in the CT rendered images to the endoscopic images. The 3D image fusion provides an interactive and intuitive guidance for surgeon by visualizing a combined and correlated relationship of the multiple imaging modalities. The 3D Magic Lens helps to effectively visualize laryngeal anatomical structures by applying different transparencies and transfer functions to the region of interest. The preliminary results of the study demonstrated that the proposed method can be readily extended for image-guided surgery of real patients.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2006년도 학술대회 2부
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• pp.577-582
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• 2006

본 논문에서는 내용 기반 영상 검색 기술을 이용하여 사용자가 원하는 영상을 쉽게 찾아내고, 이를 자동 재구성함으로써, 영화 미학의 핵심 중 하나인 몽타주 기법을 사용자 중심의 관점에서 구현하고자 한다. 본 논문에서 제안하는 실시간 몽타주 시스템은 이산 푸리에 변환(Discrete Fourier Transform)을 이용해 사용자가 선택한 영상의 특징을 찾고, 유클리디안 거리(Euclidean Distance)를 이용해 데이터베이스에 있는 영상과 유사도를 비교함으로써, 빠르고 효과적으로 사용자가 원하는 영상을 검색할 수 있다. 또한 카메라 트래킹에 의해 실시간으로 사용자의 움직임 영상을 취득하고, 취득된 영상을 검색된 사용자의 영상과 함께 자동 재구성함으로써, 손쉽게 사용자의 의도에 맞춘 영상 재구성을 하게 된다. 본 시스템은 사용자가 일방적으로 영상을 시청, 감상하는 소극적 영상의 소비자에서 벗어나, 기존의 영상을 이용해 임의의 영상을 조합하고 자기 자신의 영상까지 실시간으로 개입할 수 있도록 함으로써, 영상을 새롭게 구성하고 영상 재생산의 적극적 주체가 되는 사용자 중심의 새로운 영화(뉴미디어)의 토대가 될 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권3호
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• pp.539-557
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• 2013

A novel multifocus image fusion algorithm based on NSCT is proposed in this paper. In order to not only attain the image focusing properties and more visual information in the fused image, but also sensitive to the human visual perception, a local multidirection variance (LEOV) fusion rule is proposed for lowpass subband coefficient. In order to introduce more visual saliency, a modified local contrast is defined. In addition, according to the feature of distribution of highpass subband coefficients, a direction vector is proposed to constrain the modified local contrast and construct the new fusion rule for highpass subband coefficients selection The NSCT is a flexible multiscale, multidirection, and shift-invariant tool for image decomposition, which can be implemented via the atrous algorithm. The proposed fusion algorithm based on NSCT not only can prevent artifacts and erroneous from introducing into the fused image, but also can eliminate 'block effect' and 'frequency aliasing' phenomenon. Experimental results show that the proposed method achieved better fusion results than wavelet-based and CT-based fusion method in contrast and clarity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4476-4490
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• 2017

The aim of image annotation is to determine labels that can accurately describe the semantic information of images. Many approaches have been proposed to automate the image annotation task while achieving good performance. However, in most cases, the semantic similarities of images are ignored. Towards this end, we propose a novel Visual-Semantic Nearest Neighbor (VS-KNN) method by collectively exploring visual and semantic similarities for image annotation. First, for each label, visual nearest neighbors of a given test image are constructed from training images associated with this label. Second, each neighboring subset is determined by mining the semantic similarity and the visual similarity. Finally, the relevance between the images and labels is determined based on maximum a posteriori estimation. Extensive experiments were conducted using three widely used image datasets. The experimental results show the effectiveness of the proposed method in comparison with state-of-the-arts methods.

• 대한방사선기술학회지:방사선기술과학
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• 제45권2호
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• pp.117-125
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• 2022

Although stationary inverse-geometry digital tomosynthesis (s-IGDT) is able to reduce motion artifacts, image acquisition time and radiation dose, the image quality of the s-IGDT is degraded due to the truncations arisen in projections. Therefore, the effects of geometric and image acquisition conditions in the s-IGDT should be analyzed for improving the image quality and clinical applicability of the s-IGDT system. In this study, the s-IGDT images were obtained with the various X-ray source arrangement types and the various number of projections. The resolution and noise characteristics of the obtained s-IGDT images were evaluated, and the characteristics were compared with those of the conventional DT images. The s-IGDT system using linear X-ray source arrangement and 40 projections maximized the image characteristics of resolution and noise, and the corresponding system was superior to the conventional DT system in terms of image resolution. In conclusion, we expect that the s-IGDT system can be used for providing medical images in diagnosis.

• 전자공학회논문지
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• 제50권12호
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• pp.150-158
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• 2013

본 논문에서는 절단된 제약적 최소 제곱 필터를 이용하여 방향 적응적으로 영상을 복원하는 방법을 제안한다. 제안하는 영상복원 필터는 공간영역에서 이론적으로 영상 전체의 크기를 갖는 제약적 최소 제곱(constrained least squares; CLS) 필터를 Maxwell-Boltzmann 커널을 사용하여 절단한 유한 임펄스 응답(finite impulse response; FIR) 필터의 구조로 실시간 영상복원을 가능하게 한다. 또한 화소 단위로 공분산 행렬을 분석하여 방향성을 추정하여, 화소마다 필터의 계수를 적응적으로 생성하여 방향 적응적으로 영상을 복원한다. 실험결과를 통해 기존의 알고리듬에 비해 제안된 방법이 선명하고 부작용(artifacts)이 적은 결과를 얻는 것을 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권4호
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.

• 대한전자공학회논문지SP
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• 제46권1호
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• pp.7-13
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• 2009

본 논문은 디지털 자동초점을 위한 등방성 점확산함수 추정에 관한 새로운 방법을 제안한다. 제안하는 알고리듬은 영상의 윤곽에서 방향을 판단하고 방향에 따라 윤곽 프로파일을 수집한다. 수집한 윤곽 프로파일을 평균하여 계단응답을 만들고 등방성 점확산함수의 특징을 이용하여 점확산함수를 추정한다. 실험을 통해 열화된 영상에서 제안하는 알고리듬으로 점확산함수를 추정하는 과정을 보이고 정확성을 증명한다.