• Journal of Broadcast Engineering
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• v.14 no.1
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• pp.36-43
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• 2009

Recently, the structural similarity (SSIM) index metric is proposed. In the present paper, a new framework, which is called visual SSIM (VSSIM), is proposed by incorporating crucial human factors into the SSIM. The human factors are foveation, luminance, frequency and motion information. The performance of VSSIM is evaluated by subjective quality test compliant with the Video Quality Expert Group (VQEG) multimedia group test plan. It shows that the visual SSIM is more correlated with the subjective quality result than the conventional SSIM.

• Journal of KIISE
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• v.41 no.10
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• pp.847-858
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• 2014

Until now, a lot of image quality assessment techniques or tools for optimal human visual system(HVS)-awareness have been researched and SSIM(Structural SIMilarity) and its improved techniques are representative examples. However, they often cannot cope with various images and different distortion types robustly, and thus this can cause a large gap between their index values and HVS-awareness. In this paper, we conduct image quality assessment on SSIM and its variants intensively and analyze the causes of each component function's observed anomalies. Then, we propose a novel image quality assessment technique to compensate and improve such anomalies. Additionally, through extensive image assessment simulations, we show that the proposed technique can indicate HVS-awareness more robustly and consistently than SSIM and its variants for various images and different distortion types.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.174-180
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• 2014

In this paper, we propose the random pixel sampling technique to solve the high computational complexity in the perceptual SSIM-based backlight dimming. Specifically, the proposed algorithm selects pixels in a total frame considering the pre-defined number, and generates the block by combining these pixels. Then, it estimates parameters, which are required in the SSIM calculation, in the combined block, and hence, it can reduce the computation time significantly. In the experimental results, the proposed algorithm reduced the average power consumption and computation time by up to 38.1776 % and 99.5828 %, respectively while preserving the average SSIM., compared with the conventional algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.257-271
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• 2016

The Structural SIMilarity (SSIM) index is one of the most widely-used methods for perceptual image quality assessment (IQA). It is based on the principle that the human visual system (HVS) is sensitive to the overall structure of an image. However, it has been reported that indices predicted by SSIM tend to be biased depending on the type of distortion, which increases the deviation from the main regression curve. Consequently, SSIM can result in serious performance degradation. In this study, we investigate the aforementioned phenomenon from a new perspective and review a constant that plays a big role within the SSIM metric but has been overlooked thus far. Through an experimental study on the influence of this constant in evaluating images with SSIM, we are able to propose a new solution that resolves this issue. In the proposed IQA method, we first design a system to classify different types of distortion, and then match an optimal constant to each type. In addition, we supplement the proposed method by adding color perception-based structural information. For a comprehensive assessment, we compare the proposed method with 15 existing IQA methods. The experimental results show that the proposed method is more consistent with the HVS than the other methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.81-82
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• 2017

본 논문에서는 PSNR 을 높이도록 최적화된 HEVC 의 율-왜곡 최적화(RDO)를 MS-SSIM 를 높이도록 하여 RDO 를 수행 하도록 한다. 구현 방법으로는 MS-SSIM 도출 방법과 비슷하도록 원본과 4 단계의 저역 통과 필터(LPF)를 통과한 결과에 대한 DCT(Discrete Cosine Transform) 를 수행하고 그 AC 계수의 비율로 lagrange multiplier(${\lambda}$)를 수정하는 방식이다. AC 계수 비율과 MS-SSIM 에서 도출 된 가중치, LPF 특성 등에 따라 새롭게 각 스케일의 가중치를 결정하여 최종적으로 ${\lambda}$ 가중치를 결정하여 그 결과를 바탕으로 RDO 를 수행한다. 시뮬레이션을 통해 제안의 방법과 HEVC reference software 의 BD-rate 계산 결과 7%의 PNSR, -13.2%의 MS-SSIM 를 얻을 수 있었고 이에 따라 주관적 화질을 개선했다고 할 수 있다.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.911-912
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• 2008

In the present paper, a new framework, which is called visual SSIM (VSSIM), is proposed by incorporating crucial human factors into the SSIM. The human factors are foveation, luminance, frequency and motion information. Subjective quality test compliant with the Video Quality Expert Group (VQEG) multimedia group test plan shows that the visual SSIM is more correlated with the subjective quality result than the conventional SSIM.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.775-784
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• 2019

Image stitching is a technique for solving the problem of narrow field of view of a camera by composing multiple images. Recently, as the use of content such as Panorama, Super Resolution, and 360 VR increases, the need for faster and more accurate image stitching technology is increasing. So far, many algorithms have been proposed to satisfy the required performance, but the objective evaluation method for measuring the accuracy has not been standardized. In this paper, we present the problems of PSNR and SSIM(Structural similarity index method) measurement methods and propose a Local Differential Pixel Mean method. The LDPM evaluation method that includes geometric similarity and brightness measurement information is proved through a test, and the advantages of the evaluation method are revealed through comparison with SSIM.

• Progress in Medical Physics
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• v.26 no.4
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• pp.258-266
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• 2015

The modern radiotherapy technique which delivers a large amount of dose to patients asks to confirm the positions of patients or tumors more accurately by using X-ray projection images of high-definition. However, a rapid increase in patient's exposure and image information for CT image acquisition may be additional burden on the patient. In this study, by introducing structural similarity (SSIM) index that can effectively extract the structural information of the image, we analyze the differences between daily acquired x-ray images of a patient to verify the accuracy of patient positioning. First, for simulating a moving target, the spherical computational phantoms changing the sizes and positions were created to acquire projected images. Differences between the images were automatically detected and analyzed by extracting their SSIM values. In addition, as a clinical test, differences between daily acquired x-ray images of a patient for 12 days were detected in the same way. As a result, we confirmed that the SSIM index was changed in the range of 0.85~1 (0.006~1 when a region of interest (ROI) was applied) as the sizes or positions of the phantom changed. The SSIM was more sensitive to the change of the phantom when the ROI was limited to the phantom itself. In the clinical test, the daily change of patient positions was 0.799~0.853 in SSIM values, those well described differences among images. Therefore, we expect that SSIM index can provide an objective and quantitative technique to verify the patient position using simple x-ray images, instead of time and cost intensive three-dimensional x-ray images.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.503-513
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• 2020

This paper presents a method to evaluate denoising filters based on edge locations in their denoised images. Image quality assessment has often been performed by using structural similarity (SSIM). However, SSIM does not provide clearly the geometric accuracy of features in denoised images. Thus, in this paper, a method to localize edge locations with subpixel accuracy based on adaptive weighting of gradients is used for obtaining the subpixel locations of edges in ground truth image, noisy images, and denoised images. Then, this paper proposes a method to evaluate the geometric accuracy of edge locations based on root mean squares error (RMSE) and jaggedness with reference to ground truth locations. Jaggedness is a measure proposed in this study to measure the stability of the distribution of edge locations. Tested denoising filters are anisotropic diffusion (AF), bilateral filter, guided filter, weighted guided filter, weighted mean of patches filter, and smoothing filter (SF). SF is a simple filter that smooths images by applying a Gaussian blurring to a noisy image. Experiments were performed with a set of simulated images and natural images. The experimental results show that AF and SF recovered edge locations more accurately than the other tested filters in terms of SSIM, RMSE, and jaggedness and that SF produced better results than AF in terms of jaggedness.

• Journal of KIISE
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• v.42 no.10
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• pp.1294-1302
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• 2015

A lot of image quality assessment metrics that can precisely reflect the human visual system (HVS) have previously been researched. The Structural SIMilarity (SSIM) index is a remarkable HVS-aware metric that utilizes structural information, since the HVS is sensitive to the overall structure of an image. However, SSIM fails to deal with color difference in terms of the HVS. In order to solve this problem, the Structural and Hue SIMilarity (SHSIM) index has been selected with the Hue, Saturation, Intensity (HSI) model as a color space, but it cannot reflect the HVS-aware color difference between two color images. In this paper, we propose a new image quality assessment method for a color image by using a CIE Lab color space. In addition, by using a support vector machine (SVM) classifier, we also propose an optimization system for applying optimal metric according to the types of distortion. To evaluate the proposed index, a LIVE database, which is the most well-known in the area of image quality assessment, is employed and four criteria are used. Experimental results show that the proposed index is more consistent with the other methods.