267,732 research outputs found

    Regional Differential Information Entropy for Super-Resolution Image Quality Assessment

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    PSNR and SSIM are the most widely used metrics in super-resolution problems, because they are easy to use and can evaluate the similarities between generated images and reference images. However, single image super-resolution is an ill-posed problem, there are multiple corresponding high-resolution images for the same low-resolution image. The similarities can't totally reflect the restoration effect. The perceptual quality of generated images is also important, but PSNR and SSIM do not reflect perceptual quality well. To solve the problem, we proposed a method called regional differential information entropy to measure both of the similarities and perceptual quality. To overcome the problem that traditional image information entropy can't reflect the structure information, we proposed to measure every region's information entropy with sliding window. Considering that the human visual system is more sensitive to the brightness difference at low brightness, we take γ\gamma quantization rather than linear quantization. To accelerate the method, we reorganized the calculation procedure of information entropy with a neural network. Through experiments on our IQA dataset and PIPAL, this paper proves that RDIE can better quantify perceptual quality of images especially GAN-based images.Comment: 8 pages, 9 figures, 4 table

    Real-time dynamic image-source implementation for auralisation

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    This paper describes a software package for auralisation in inter- active virtual reality environments. Its purpose is to reproduce, in real time, the 3D soundfield within a virtual room where listener and sound sources can be moved freely. Output sound is presented binaurally using headphones. Auralisation is based on geometric acoustic models combined with head-related transfer functions (HRTFs): the direct sound and reflections from each source are computed dynamically by the image-source method. Directional cues are obtained by filtering these incoming sounds by the HRTFs corresponding to their propagation directions relative to the listener, computed on the basis of the information provided by a head-tracking device. Two interactive real-time applications were developed to demonstrate the operation of this software package. Both provide a visual representation of listener (position and head orientation) and sources (including image sources). One focusses on the auralisation-visualisation synchrony and the other on the dynamic calculation of reflection paths. Computational performance results of the auralisation system are presented

    Digital Image Steganography Based On Integer Haar Wavelet Transform And Coefficient Difference

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    The development of digital information led to the demand for information security technology that protects the confidentiality of information. Digital steganography is one of such technology that able to protect the information from illegal interception due to its capability to hide the existence of the information without attracting the eavesdropper‟s attention. Among digital media, digital image is the most widely used media for steganography. Discrete Cosine Transform (DCT) is a well-known technique in digital image steganography, but the block calculation of DCT may pose artifact on the images. The disadvantages of DCT can be eliminating by the Discrete Wavelet Transform (DWT) which is more compatible with the Human Visual System (HVS). However the floating point of DWT can causes loss of information. On the other hand, Integer Wavelet Transform (IWT) is represented in finite precision numbers, which can avoid the problem of floating point precision of DWT. In this study, the messages are embedded on the wavelet coefficients of 1-level Integer Haar Wavelet Transform (IHWT) using Coefficient Difference scheme that adopted from Pixel Value Differencing (PVD). The messages are embedded on the difference value of two adjacent wavelet coefficients. Peak Signal to Noise Ration (PSNR) and Structural Similarity (SSIM) are used to measure the quality of stego image. The result shows that the proposed method has outperformed the existing method that employ IHWT and Pixel Mapping Method (PMM) in term of capacity vs. imperceptibility, as well as the maximum capacity. This is due to the high degree of Coefficient Difference that can tolerate larger modification of wavelet coefficients. Moreover, the Coefficient Difference can be applied on all coefficients instead of either significant or insignificant coefficient. These lead to the both high capacity and imperceptibility of digital image steganography system

    Wavelet-Based Image Registration and Segmentation Framework for the Quantitative Evaluation of Hydrocephalus

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    Hydrocephalus, characterized by increased fluid in the cerebral ventricles, is traditionally evaluated by a visual assessment of serial CT scans. The complex shape of the ventricular system makes accurate visual comparison of CT scans difficult. The current research developed a quantitative method to measure the change in cerebral ventricular volume over time. Key elements of the developed framework are: adaptive image registration based on mutual information and wavelet multiresolution analysis; adaptive segmentation with novel feature extraction based on the Dual-Tree Complex Wavelet Transform; volume calculation. The framework, when tested on physical phantoms, had an error of 2.3%. When validated on clinical cases, results showed that cases deemed to be normal/stable had a calculated volume change less than 5%. Those with progressive/treated hydrocephalus had a calculated change greater than 20%. These findings indicate that the framework is reasonable and has potential for development as a tool in the evaluation of hydrocephalus

    A Method of Cubic Object Feature Extraction

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    How to reduce and simplify the calculation for image recognition is a very attractive and important issue in order to realize the real time control of a robot based on the image recognition results. This paper describes a method of extracting 2 - dimensional geometrical features of cubic objects based on the normal vector distributions from the visual information obtained with the laser range finder to reduce the calculation of the image recognition. In this research a laser beam is scanned in the horizontal plane to which the cubic objects stand vertically and the laser spot is detected with a TV camera every sampling time. These spots make an intermittent locus which includes some special lines corresponding to the cubic objects. To extract the features of the cubic objects, we utilize the normal vectors formed on the locus. If some normal vectors distribute in the same direction and the origin of the normal vectors are very close to their neighbor's, these normal vectors can be classified into the same class, -the straight line class. Because the normal vectors on the neighbor surfaces of the cubic objects are vertical to each other, we use this property to determine the pair of straight lines which belong to the cubic objects. Making the histogram based on the normal vectors with the same direction, we obtain the peaks which are supported by the points on the cubic object surfaces. Then, the points can be extracted from the set of points on the whole locus inversely according to the relations with the peaks and the features of the cubic object can be extracted by applying method of least square to these extracted points. The experiments proved the availability of the proposed processing algorithm

    A Method to Evaluate the Stimulation of a Real World Field of View by Means of a Spectroradiometric Analysis

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    Stimulation elicited by a real world field of view is related to the color, the intensity and the direction of the information reaching the eye: different spectral power distributions of light trigger different responses. An evaluation of the stimulation provided by the field of view can be performed by measuring the spectral radiance with a spectroradiometer and weighting this data with an efficiency curve. Different weights (physical, physiological and psychological) can lead to different analyses and consequently to different results. The proposed method allows an overall and simplified evaluation of the field of view based on spectral and luminance measures and a script that processes the luminous information. The final aim of this approach is to provide further information about the light stimulation reaching the retina and to supply a qualitative evaluation of the field of view, allowing to know how much stimulation is coming from a certain area within the visual field depending on the type of surface, basing on spectral and directional information. This approach can have practical implications, allowing technicians and designers to take into consideration the possible visual fields, in order to properly shape the features of stimulation throughout the day, hence following a field of view-based dynamic design
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