- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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An image segmentation method of a modified SPCNN based on human visual system in medical images
摘要： An image segmentation method of a modified simplified pulse-coupled neural network (MSPCNN) based on human visual system (HVS) is proposed for medical images. The method successfully determines the stimulus input of the MSPCNN according to the characteristics of PCNN and HVS. In order to accomplish the goal, we attempt to deduce the sub-intensity range of central neurons firing by introducing neighboring firing matrix Q and calculating intensity distribution range based on a new MSPCNN(NMSPCNN), and then reveal the way how sub-intensity range parameter Sint generates the stimulus input Sioij closer to HVS. Besides, we try to substitute the above stimulus input into the MSPCNN to extract more suitable lesions for medical images. In contrast to prevalent PCNN models, the MSPCNN has higher segmentation accuracy rates and lower computational complexity because of the parameter setting method. Finally, the proposed method comparing with the state-of-the-art methods has a better performance, presenting the overall metric OEM with MIAS of 0.8784, DDSM of 0.8606 and gallstones of 0.8585.
关键词： Sub-intensity Range,Modified Simplified Pulse-coupled Neural Network,Image Segmentation,Stimulus Input,Human Visual System
更新于2025-09-23 15:23:52
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Blind Quality Index for Tone-Mapped Images Based on Luminance Partition
摘要： Tone-mapping operators (TMOs), which are designed to convert high dynamic range (HDR) images to standard low dynamic range (LDR) images for displaying on conventional devices, have gained extensive attention recently. The quality of tone-mapped images generated by different TMOs varies significantly, which depends upon the image contents and the parameter settings. A quality index that can accurately evaluate the performances of TMOs is thus highly needed. With this motivation, this paper presents a blind quality index based on luminance partition for tone-mapped images. It is based on the fact that the Human Visual System (HVS) has different sensitivities to image regions with different luminance levels. Specifically, two adaptive thresholds are first employed to segment an image into the dark, bright and normal areas. Then, we calculate the quality-aware features from different luminance areas: 1) local entropy feature is extracted from the dark and bright areas to measure the information loss due to the overexposure or underexposure during the tone mapping process; 2) local colorfulness feature is extracted from the normal area to evaluate the reproduction of colors. With the consideration that the perception of image quality depends on the combined effects of the salient local distortion and global quality degradation, the global contrast feature is also calculated and integrated for better evaluation performance. Moreover, to take advantage of the hierarchical characteristic of the HVS, all features are calculated under a multi-resolution framework. Eventually, the extracted features are mapped into an objective quality score based on the random forest regression. The proposed metric is shown to outperform those state-of-the-art metrics according to extensive experiments conducted on two publicly available databases.
关键词： tone-mapped image,multi-resolution representation,Tone-mapping operators,random forest regression,luminance partition,human visual system
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - Shenzhen, China (2018.7.13-2018.7.15)] 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - A Lightweight Quality Assessment of Screen Content Images using Directional Derivative Filters
摘要： In this paper, we present a lightweight visual quality assessment of screen content image (SCI) based on the local luminance edge directions and gradient magnitude. First, we use directional derivative filters (DDFs) to extract the edge direction feature which is one of the main characteristics of SCIs. To obtain the perceptual quality measures, we separately extract the edge direction and gradient magnitude for the similarity computation between the reference and distorted SCIs. Finally, considering the computational complexity, we incorporate the DDF-based feature map with the gradient magnitude map together to generate a new visual quality metric. Experimental results have demonstrated that the proposed method is able to adapt better to the human visual system than 12 representative methods based on the screen image quality assessment database (SIQAD).
关键词： screen content images,directional derivatives,Image quality assessment (IQA),human visual system
更新于2025-09-23 15:22:29
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Efficiency in Street Lighting Projects by Employing LED Luminaires and Mesopic Photometry
摘要： This paper discusses the importance of adapting conventional photometric quantities when lighting systems with low luminance levels are under analysis, as public lighting or external lighting in general. In this sense, it is presented an alternative methodology for lighting projects in street lighting, considering the mesopic photometry. The CIE recommendation 191:2010 proposes correction factors that convert conventional photometric quantities (photopic) into quantities adapted to the corresponding mesopic level. However, a necessary parameter to obtain these correction factors is the relationship between the scotopic and photopic light fluxes of a light source (S/P ratio), which requires special equipment that it is not easily available to engineers, technicians and lighting designers. Thus, this paper proposes a general equation that provides the S/P ratio as a function of the correlative color temperature and the color rendering index of the light source, which are information provided in the manufacturers’ catalogs or electric lamp packages. To illustrate the application of the experimentally derived relationship, a typical street lighting project is considered, specifically a retrofit from HPS lamps to modern LED luminaires. In this case, the conventional routine must be changed, allowing the adaptation of conventional quantities to mesopic quantities without need for specialized equipment. The case study evidences that the use of mesopic photometry in conjunction with more appropriate technologies, such as LED luminaires, lead to a higher energy efficiency of the system.
关键词： Scotopic/photopic ratio,Human visual system,Mesopic vision,CIE 191:2010 report,Street lighting,Photometry,outdoor lighting,energy efficiency
更新于2025-09-12 10:27:22
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Generating Image Distortion Maps Using Convolutional Autoencoders with Application to No Reference Image Quality Assessment
摘要： We present two contributions in this work: (i) a reference-free image distortion map generating algorithm for spatially localizing distortions in a natural scene, and (ii) no reference image quality assessment (NRIQA) algorithms derived from the generated distortion map. We use a convolutional autoencoder (CAE) for distortion map generation. We rely on distortion maps generated by the SSIM image quality assessment (IQA) algorithm as the “ground truth” for training the CAE. We train the CAE on a synthetically generated dataset composed of pristine images and their distorted versions. Specifically, the dataset was created by applying standard distortions such as JPEG compression, JP2K compression, Additive White Gaussian Noise (AWGN) and blur to the pristine images. SSIM maps are then generated on a per distorted image basis for each of the distorted images in the dataset and are in turn used for training the CAE. We first qualitatively demonstrate the robustness of the proposed distortion map generation algorithm over several images with both traditional and authentic distortions. We also demonstrate the distortion map’s effectiveness quantitatively on both standard distortions and authentic distortions by deriving three different NRIQA algorithms. We show that these NRIQA algorithms deliver competitive performance over traditional databases like LIVE Phase II, CSIQ, TID 2013, LIVE MD and MDID 2013, and databases with authentic distortions like LIVE Wild and KonIQ-10K. In summary, the proposed method generates high quality distortion map that are used to design robust NRIQA algorithms. Further, the CAE based distortion maps generation method can easily be modified to work with other ground truth distortion maps.
关键词： Convolutional neural network,no reference image quality assessment (IQA),human visual system (HVS),autoencoders
更新于2025-09-11 14:15:04