- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Multichannel image contrast enhancement based on linguistic rule-based intensificators
摘要： This study follows the direct approach to image contrast enhancement, which changes the image contrast at each its pixel and is more effective than the indirect approach that deals with image histograms. However, there are only few studies following the direct approach because, by its nature, it is very complex. Additionally, it is difficult to develop an effective method since it is required to keep a balance in maintaining local and global image features while changing the contrast at each individual pixel. Moreover, raw images obtained from many sources randomly influenced by many external factors can be considered as fuzzy uncertain data. In this context, we propose a novel method to apply and immediately handle expert fuzzy linguistic knowledge of image contrast enhancement to simulate human capability in using natural language. The formalism developed in the study is based on hedge algebras considered as a theory, which can immediately handle linguistic words of variables. This allows the proposed method to produce an image contrast intensificator from a given expert linguistic rule base. A technique to preserve global as well as local image features is proposed based on a fuzzy clustering method, which is applied for the first time in this field to reveal region image features of raw images. The projections of the obtained clusters on each channel are suitably aggregated to produce a new channel image considered as input of the pixelwise defined operators proposed in this study. Many experiments are performed to demonstrate the effect of the proposed method versus the counterparts considered.
关键词： interpolation inference method,contrast measurement,image contrast enhancement,hedge algebra,linguistic rule-based knowledge
更新于2025-09-23 15:23:52
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Real time video image enhancement approach using particle swarm optimisation technique with adaptive cumulative distribution function based histogram equalization
摘要： Recent years, real time videos are playing an important role in different applications such as pattern recognition, security purpose, news analysis, weather digest, and video browser and so on. Due to the importance of real time video applications, the quality of the real time video must be improved for making effective results in real time video analysis process. This paper introduces the particle optimization with adaptive cumulative distribution based histogram enhancement technique (PACDHE) for improving the real time video quality. Initially the videos are collected, each incoming frame has been analyzed and noise present in the video frame is eliminated by applying the non-divisional median filter. After that, quality of real time video is enhanced iteratively by examining each pixel present in video frames using the optimized fitness and cumulative distribution function. This process is repeated continuously until to enhance the real time video frames contrast and quality. Then the performance of the system is analyzed by using CV online video database and the efficiency is examined in terms of peak signal to noise ratio (PSNR), Absolute Mean Brightness Error (AMBE) and Entropy. The experimental results of PSO are compared with genetic algorithm based approach and found that PSO outperforms the GA approach and the existing histogram equalization approach and the existing histogram equalization approaches.
关键词： contrast enhancement,particle optimization based adaptive cumulative distribution based histogram enhancement technique (PACDHE),fitness and cumulative distribution function,CV online video database,Video quality
更新于2025-09-23 15:23:52
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An Efficient Approach to Restore Naturalness of Non-uniform Illumination Images
摘要： Enhancement of the image details without affecting the naturalness is a difficult task, especially for non-uniformly illuminated images. While dealing with non-uniformly illuminated images, most of the available image enhancement approaches show common drawbacks such as loss of naturalness and appearance of artifacts in the resultant image. It is very difficult to maintain a trade-off between detail enhancement and naturalness. To deal with this problem, we propose an efficient approach for enhancing local details as well as the color information and preserve the naturalness in the resultant image. The proposed method is effectively enhancing the local details, along with the visibility of the image (having dark and bright regions) without affecting the naturalness. Experimental results also support our claims and confirmations that the proposed approach outperforms other state-of-the-art methods.
关键词： Color preservation,Naturalness preservation,Image enhancement,Contrast enhancement
更新于2025-09-23 15:22:29
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[IEEE 2018 OCEANS - MTS/IEEE Kobe Techno-Ocean (OTO) - Kobe, Japan (2018.5.28-2018.5.31)] 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO) - Multi-Scale Gradient Domain Underwater Image Enhancement
摘要： Underwater images often suffer from low visibility, due to the attenuation and scattering of the propagated light, which are caused by the dense and non-uniform medium. Based on the observation that degradation of underwater images occurs both in contrast and color, this paper aims at compensating the contrast and color saturation of the image respectively. To achieve this, we first white balance the degraded image to remove the color casts while producing a natural appearance of the underwater image. Then propose a multi-scale gradient domain contrast enhancement strategy to increase the visibility, and compensate the attenuation of color saturation according to the estimated transmission. Both qualitative and quantitative results demonstrate the effectiveness of the proposed method. Our method yields accurate results with significantly enhanced contrast and superior color, even better than other state-of-the-art methods.
关键词： Underwater image,Gradient Domain,Contrast enhancement,Edge-preserving image decomposition,Color correction
更新于2025-09-23 15:22:29
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Low-light Image Enhancement by Principal Component Analysis
摘要： Under extreme low-lighting conditions, images have low contrast, low brightness, and high noise. In this paper, we propose a principal component analysis framework to enhance low-light-level images with decomposed luminance–chrominance components. A multi-scale retinex-based adaptive filter is developed for the luminance component to enhance contrast and brightness significantly. Noise is attenuated by a proposed collaborative filtering employed to both the luminance and chrominance components that reveal every finest detail by preserving the unique features in the image. To evaluate the effectiveness of the proposed algorithm, a simulation model is proposed to generate nighttime images for various levels of contrast and noise. The proposed algorithm can process a wide range of images without introducing ghosting and halo artifacts. The quantitative performance of the algorithm is measured in terms of both full-reference and blind performance metrics. It shows that the proposed method delivers state-of-the-art performance both in terms of objective criteria and visual quality compared to the existing methods.
关键词： denoising,Contrast enhancement,principal component analysis
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE 8th International Conference on Consumer Electronics - Berlin - Berlin, Germany (2018.9.2-2018.9.5)] 2018 IEEE 8th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) - Context-Aware Contrast Enhancement Using Shadow Region Estimation and Bright Channel
摘要： This paper presents a contrast image enhancement method using a shadow region estimation and bright channel. To separate the dark and bright regions, the proposed method estimates the shadow map by selecting the darkest pixels of a low-contrast image. The bright channel represents the brightest pixel among the red, green, and blue pixels and it preserves the bright region of an input image. The resulting image is obtained by synthesizing the input and brightness enhance images using shadow map and bright channel. Experimental results show that the proposed method can provide the enhanced images without undesired artifact brightness saturation and color distortion.
关键词： Contrast enhancement,Shadow estimation,Bright channel prior
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) - Kiev (2018.4.24-2018.4.26)] 2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) - Automatic Enhancement of Low-Contrast Monochrome Images
摘要： The problem of images enhancement in automatic mode with an acceptable level of computational costs is considered. The task of adaptive enhancement of integral contrast for complex monochrome images on the basis of their nonlinear statistical non-inertial transformations is considered. The research of the effectiveness of the main histogram-based methods of enhancement of the integral contrast of complex images with low-contrast small-sized objects and non-uniform illumination is carried out. A comparative analysis of the effectiveness of no-reference assessing the generalized contrast of complex images using the histogram-based metrics of integral contrast and on the basis of expert assessments is carried out.
关键词： image processing,image quality,low-contrast objects,automatic mode,contrast enhancement
更新于2025-09-19 17:15:36
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Quantitative imaging biomarkers for Yttrium-90 distribution on Bremsstrahlung single photon emission computed tomography after resin-based radioembolization
摘要： To identify baseline imaging features in patients with liver cancer that correlate with Yttrium-90 (90Y) distribution on post-procedural single photon emission computed tomography (SPECT) and predict tumor response to transarterial radioembolization (TARE). Methods: This retrospective study was approved by the institutional review board and included 38 patients with hepatocellular carcinoma (HCC) (n = 23, 18/23 males, mean age 62.39±8.62 years, 34 dominant tumors) and non-HCC hepatic malignancies (n = 15, 9/15 males, mean age 61.13±11.51 years, 24 dominant tumors) who underwent 40 resin-based TARE treatments (08/2012-01/2018). Multi-phasic contrast-enhanced MRI or CT was obtained prior to and Bremsstrahlung SPECT within two hours after TARE. Total (TTV, cm3) and enhancing tumor volume (ETV, cm3 and % of TTV), and total and enhancing tumor burden (%) were volumetrically assessed on baseline imaging. Up to two dominant tumors per treated lobe were analyzed. After multimodal image registration of baseline imaging and SPECT/CT (MIM Software Inc., Cleveland, OH), 90Y distribution was quantified on SPECT as tumor-to-normal-liver-ratio (TNR). Response was assessed according to RECIST1.1 and quantitative European Association for the Study of the Liver (qEASL) criteria. Clinical parameters were also assessed. Statistical tests included Mann-Whitney-U, Pearson correlation, and linear regression. Results: In HCC patients, high baseline ETV% significantly correlated with high TNR on SPECT, demonstrating greater 90Y uptake in the tumor relative to the liver parenchyma (p < 0.001). In non-HCC patients, a correlation between ETV% and TNR was observed as well (p = 0.039). Follow-up imaging for response assessments within one to four months post-TARE was available for 23 patients with 25 treatments. The change of ETV% significantly correlated with TNR in HCC (p = 0.039) but not in non-HCC patients (p = 0.886). Additionally, Child-Pugh class B patients demonstrated significantly more 90Y deposition in non-tumorous liver compared to Child-Pugh A patients (p = 0.021). Conclusion: This study identified ETV% as a quantifiable imaging biomarker on pre-procedural MRI and CT to predict 90Y distribution on post-procedural SPECT in HCC and non-HCC. However, the relationship between the preferential uptake of 90Y to the tumor with tumor response after radioembolization could only be validated for HCC.
关键词： imaging biomarker,Radioembolization,quantitative SPECT,Yttrium-90,contrast enhancement
更新于2025-09-19 17:15:36
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[IEEE 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Honolulu, HI, USA (2018.7.18-2018.7.21)] 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Introducing a Novel Layer in Convolutional Neural Network for Automatic Identification of Diabetic Retinopathy
摘要： Convolutional neural networks have been widely used for identifying diabetic retinopathy on color fundus images. For such application, we proposed a novel framework for the convolutional neural network architecture by embedding a preprocessing layer followed by the first convolutional layer to increase the performance of the convolutional neural network classifier. Two image enhancement techniques i.e. 1- Contrast Enhancement 2- Contrast-limited adaptive histogram equalization were separately embedded in the proposed layer and the results were compared. For identification of exudates, hemorrhages and microaneurysms, the proposed framework achieved the total accuracy of 87.6%, and 83.9% for the contrast enhancement and contrast-limited adaptive histogram equalization layers, respectively. However, the total accuracy of the convolutional neural network alone without the prreprocessing layer was found to be 81.4%. Consequently, the new convolutional neural network architecture with the proposed preprocessing layer improved the performance of convolutional neural network.
关键词： contrast-limited adaptive histogram equalization,contrast enhancement,preprocessing layer,diabetic retinopathy,Convolutional neural networks,image enhancement
更新于2025-09-10 09:29:36
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Improved Image Fusion of Colored and Grayscale Medical Images Based on Intuitionistic Fuzzy Sets
摘要： Image fusion is the process of combining the properties of two images into one single image that will show the features of both the images. There are various methods available in the literature to fuse the images. In this paper, an intuitionistic fuzzy logic-based image fusion approach has been implemented for medical images that firstly suppresses the noise and enhances the input images, and merges them efficiently in Hue-Saturation-Intensity domain. Here, enhancement is included because these input images are not always well contrasted and may contain some noise due to the inherent properties of the modalities used for capturing the images. The intuitionistic fuzzy sets are incorporated to handle uncertainties that are often due to vagueness and ambiguity. The results certify that this method significantly improves the output fused image than the image obtained by existing technique both visually and metrically.
关键词： fuzzy histogram equalization,Image fusion,contrast enhancement,intuitionistic fuzzy sets
更新于2025-09-10 09:29:36