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The contrast of an image can be degraded by the presence of background light and sensor noise. To overcome this degradation, quantum illumination protocols have been theorised (Science 321 (2008), Physics Review Letters 101 (2008)) that…
One of the most surprising consequences of quantum mechanics is the entanglement of two or more distant particles. Although questions regarding fundamental issues of quantum theory still exist, quantum entanglement has started to play…
Quantum imaging is an advanced method for microscopy or investigating the optical properties of materials or bio-medical inspections with high accuracy, low noise, and extremely low photo-damage. In previous work, we proposed a quantum…
A novel technique for polarization-multiplexing ghost imaging is proposed to simultaneously obtain multiple polarimetric information by a single detector. Here, polarization-division multiplexing speckles are employed for object…
Color distortion can introduce a significant damage in visual quality perception, however, most of existing reduced-reference quality measures are designed for grayscale images. In this paper, we consider a basic extension of well-known…
The capability of image semantic segmentation may be deteriorated due to noisy input image, where image denoising prior to segmentation helps. Both image denoising and semantic segmentation have been developed significantly with the advance…
In the last few years,the field of ghost imaging has seen many new developments. From computational ghost imaging to 3D ghost imaging, this field has shown many interesting applications. But the method of obtaining an image in ghost imaging…
Image quality is an important practical challenge that is often overlooked in the design of machine vision systems. Commonly, machine vision systems are trained and tested on high quality image datasets, yet in practical applications the…
Binarization of degraded document images is an elementary step in most of the problems in document image analysis domain. The paper re-visits the binarization problem by introducing an adversarial learning approach. We construct a Texture…
Ghost imaging, Fourier transform spectroscopy, and the newly developed Hadamard transform crystallography are all examples of multiplexing measurement strategies. Multiplexed experiments are performed by measuring multiple points in space,…
Currently, many blind deblurring methods assume blurred images are noise-free and perform unsatisfactorily on the blurry images with noise. Unfortunately, noise is quite common in real scenes. A straightforward solution is to denoise images…
Image binarization is the process of separation of pixel values into two groups, white as background and black as foreground. Thresholding plays a major in binarization of images. Thresholding can be categorized into global thresholding and…
We present a novel algorithm for blind denoising of images corrupted by mixed impulse, Poisson, and Gaussian noises. The algorithm starts by applying the Anscombe variance-stabilizing transformation to convert the Poisson into white…
Quantization is widely applied in machine learning to reduce computational and storage costs for both data and models. Considering that classification tasks are fundamental to the field, it is crucial to investigate how quantization impacts…
Quality of image always plays a vital role in in-creasing object recognition or classification rate. A good quality image gives better recognition or classification rate than any unprocessed noisy images. It is more difficult to extract…
Images acquired by computer vision systems under low light conditions have multiple characteristics like high noise, lousy illumination, reflectance, and bad contrast, which make object detection tasks difficult. Much work has been done to…
While it is known that copying a quantum system does not increase the amount of information obtainable about the originals, it may increase the amount available in practice, when one is restricted to imperfect measurements. We present a…
Recently, the application of low rank minimization to image denoising has shown remarkable denoising results which are equivalent or better than those of the existing state-of-the-art algorithms. However, due to iterative nature of low rank…
The currently used ghost image schemes traditionally involve two-mode entangled light states or incoherent radiation. Here, application of four-mode entangled light states is considered. It is shown that multiplexed ghost images (MGI)…
Image quality is the basis of image communication and understanding tasks. Due to the blur and noise effects caused by imaging, transmission and other processes, the image quality is degraded. Blind image restoration is widely used to…