The paper presents an analysis of changes in imagequality that occur in optical system with a spectral range shift. A basic system was designed for the visible range with the prospect of receiving objectives operatin...
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ISBN:
(纸本)9781510656970;9781510656963
The paper presents an analysis of changes in imagequality that occur in optical system with a spectral range shift. A basic system was designed for the visible range with the prospect of receiving objectives operating in the range from UV to IR. In the process of transition from the wavelength of 0,55 mu m to 0,2 mu m, a dramatic drop for initially diffraction qualitysystem in the Strehl number by 1,5 times was found. However, since this criterion does not represent the features of the imagequality drop, both Strehl and other computed imagequality parameters (Rayleigh and Marechal criteria) cannot be recommended as universal requirements for systems with an unspecified spectral range. An assessing the multispectral systemimagequality by MTF is proposed. Based on this, conclusions about the initial requirements for imagequality of multispectral systems can be acquired. The conclusions are made based on the experience of designing a Schwarzschild mirror objective with a numerical aperture of 0.8 for the range of 0,21-2 mu m.
Large DOF (depth-of-field) with high SNR (signal-noise-ratio) imaging plays an important role in many applications such as unmanned driving to medical imaging. However, there is always a trade-off between DOF and SNR ...
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ISBN:
(纸本)9781510656970;9781510656963
Large DOF (depth-of-field) with high SNR (signal-noise-ratio) imaging plays an important role in many applications such as unmanned driving to medical imaging. However, there is always a trade-off between DOF and SNR in traditional optical design. In this paper, we propose a NIR&VISCAM (NIR&VIS Camera) that combines multi-spectral optical design and deep learning to realize large DOF and high SNR imaging. Specifically, a multi-spectral optical imaging system based on the HVS (human visual system) is designed to provide colorful but small DOF VIS (visible) image and large DOF NIR (near-infrared) image. To achieve DOF extension, we build a fusion network NIR&VISNet consisting of a VIS encoder for color extraction, a NIR encoder for spatial details extraction and a decoder for information fusion. We establish a prototype to capture real-scene dataset containing 1000 sets and test our method on a variety of test samples. The experimental results demonstrate that our NIR&VISCAM can effectively produce large DOF images with high quality. Moreover, compared to the classic image fusion methods, our designed algorithm achieves the optimal performance in DOF extension and color fidelity. With the prominent performance in large DOF and high SNR imaging, this novel and portable system is promising for vision applications such as smartphone photography, industry detection, and life medical.
Visual odometry (VO) system is challenged by complex illumination environments. imagequality and its consistency in the time domain directly determine feature detection and tracking performance, which further affect ...
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ISBN:
(纸本)9798350384581;9798350384574
Visual odometry (VO) system is challenged by complex illumination environments. imagequality and its consistency in the time domain directly determine feature detection and tracking performance, which further affect the robustness and accuracy of the entire system. In this paper, an image acquisition scheme with image bracketing patterns is proposed. images with different exposure levels are continuously captured to sufficiently explore the scene under varying illumination. An attribute control method is designed to adjust image exposures within the brackets online. Gaussian process regression fits the relationship between imagequality metric and exposure via image synthesis technique. The optimal exposures for the next bracket are obtained directly without attempts to ensure a quick response. Experiments show our acquisition system's effectiveness and performance improvement for VO tasks in complex illumination scenes.
Ruda designs high performance imaging systems to meet difficult mission requirements, but these nearly diffraction limited systems often have small margins between the imagequality of the nominal design and the requi...
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ISBN:
(纸本)9781510679184;9781510679191
Ruda designs high performance imaging systems to meet difficult mission requirements, but these nearly diffraction limited systems often have small margins between the imagequality of the nominal design and the required performance of the as-built system. Due to this we may spend significant resources designing and operating specialized test setups to ensure that results of MTF and ensquared energy (EE) measurements are well-calibrated and accurate. Alternatively, wavefront measurements - like those captured by wavefront sensors and interferometers - can be taken of the system to characterize the quality of the as-built system. Wavefront measurements are typically higher resolution, faster to setup, and quicker to measure than imagequality metrics, making them particularly attractive for use when validating as-built systemquality. Since the wavefront is related to the point spread function, and thereby the imagequality, different wavefront measurements can contain information about the system MTF and EE. Thus, if the relationship between the wavefront and imagequality metrics of interest can be established for an as-built system, it is possible to supplement or fully validate MTF and EE requirements from wavefront measurements. To investigate this relationship, we used Zemax OpticStudio to generate toleranced Monte Carlo trials of two nearly diffraction limited imaging systems designed by Ruda. The Monte Carlo models were then analyzed to form large data sets for statistical analysis. For wavefront data, the simulation produces single pass and double pass wavefront Zernike decompositions as well as wavefront root mean squared error over a range of object fields and visible wavelengths. For imagequality data, the MTF at three spatial frequencies and the EE at two integration lengths are computed for the same fields and wavelengths as the wavefront data. These data sets are then processed to demonstrate that high degrees of correlation can exist between wavefron
The human visual system (HVS) is important for guiding the blind imagequality assessment method (BIQA). Inspired by the free-energy principle, an NR-IQA method that simulates human visual perception is proposed. The ...
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ISBN:
(纸本)9798400709647
The human visual system (HVS) is important for guiding the blind imagequality assessment method (BIQA). Inspired by the free-energy principle, an NR-IQA method that simulates human visual perception is proposed. The whole model consists of an image restoration network and a multi-stream quality prediction network. Firstly, the distorted image is fed into the image restoration network to generate the restored images and discrepancy map, in which the quality perception constraint and the structural similarity discrepancy map-based constraint are both considered during the optimization to improve the recovery performance. Then, the distorted images, the restored images, and the perceptual discrepancy maps are utilized as inputs for the multi-stream quality prediction network to obtain their fused features. Finally, the fused features are input into the patch-based attention module to obtain the final image patch scores. Extensive experiments demonstrate that our proposed model is effective and achieves competitive performance when compared with other related state-of-the-art methods.
The purpose of this study is to build an interactive construction progress and quality monitoring system based on image processing, so as to improve the monitoring efficiency and quality management level of the constr...
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Phantom-based quality control, the current standard of QC in medical imaging, calibrates imagequality at a population level, but does not account for the influence of patient variation on quality. In this work, we pr...
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ISBN:
(纸本)9781510671553;9781510671546
Phantom-based quality control, the current standard of QC in medical imaging, calibrates imagequality at a population level, but does not account for the influence of patient variation on quality. In this work, we present a method to evaluate task-based imagequality directly in individual clinical CT exams. Noise power spectrum (NPS) is measured in selected local image regions satisfying linearity and noise stationarity constraints, and globally over the volumetric image. Together with a semi-empirical model of image resolution, NPS is used to calculate noise-equivalent quanta (NEQ), a fundamental metric of image fidelity and information content. The NEQ may be extended to task-based detectability (d') via a specified task function and model observer. We show that this method can: 1) elucidate intra-patient variations in signal detectability, and 2) task performance variations across a patient population. The method may be implemented in a hospital-wide online system that monitors imaging performance in CT exams in real-time.
This study proposes an innovative algorithm based on DCNN and multi-channel image fusion, aiming to improve the quality and efficiency of virtual scene image generation. The algorithm extracts depth information and te...
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The feasibility of using machine learning methods to generative architectural design solutions has been widely recognized as an effective in enhancing innovation, diversity, and efficiency of solutions. However, in ge...
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ISBN:
(纸本)9789887891819
The feasibility of using machine learning methods to generative architectural design solutions has been widely recognized as an effective in enhancing innovation, diversity, and efficiency of solutions. However, in generative design methods, the accuracy and quality of design results often rely on empirical evaluation of expert, which is challenging to evaluate and quantify by unified standards. This paper proposes a comprehensive method for evaluating model performance in architectural design tasks. The evaluation is based on computational criteria (i.e., FID, IS, SIMM indicators) and expert system criteria. The computational metrics will measure the distance, diversity, and similarity between the feature vectors of the real image and the generated image. In contrast, the expert criteria will measure the accuracy, intentionality, and rationality of the layout scheme. This study applies this framework to evaluate three widely used generative models in architectural design: GANs, Diffusion Models, and VAE. The framework also guides the optimization of generative models in architectural applications and assists architects in validating generative outcomes with more efficient workflows.
This paper presents a comparative study on the optical system design for a smartphone-based fundus camera to enhance retinal imaging quality. Three optical system configurations were evaluated using ANSYS Zemax OpticS...
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