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In this research paper, the authors propose a new approach to digital image compression using crack coding This method starts with the original image and develop crack codes in a recursive manner, marking the pixels visited earlier and…

Nonlinear dimensionality reduction methods have demonstrated top-notch performance in many pattern recognition and image classification tasks. Despite their popularity, they suffer from highly expensive time and memory requirements, which…

The technique of non-redundant masking (NRM) transforms a conventional telescope into an interferometric array. In practice, this provides a much better constrained point spread function than a filled aperture and thus higher resolution…

In this paper a new fractal image compression algorithm is proposed in which the time of encoding process is considerably reduced. The algorithm exploits a domain pool reduction approach, along with using innovative predefined values for…

The problem of numerical differentiation can be thought of as an inverse problem by considering it as solving a Volterra equation. It is well known that such inverse integral problems are ill-posed and one requires regularization methods to…

Depth estimation using a single-photon LiDAR is often solved by a matched filter. It is, however, error-prone in the presence of background noise. A commonly used technique to reject background noise is the rank-ordered mean (ROM) filter…

Silicon photomultipliers (SiPMs) are currently the most prevalent photon detection technology in modern experiments in high-energy physics, astroparticle physics, neutrino physics, and dark matter searches. The high detection efficiency for…

In this paper, we analyze and discuss ShadowFormer in preparation for the NTIRE2023 Shadow Removal Challenge [1], implementing five key improvements: image alignment, the introduction of a perceptual quality loss function, the…

Fourier ptychographic microscopy (FPM) is a recently proposed computational imaging technique with both high resolution and wide field-of-view. In current FP experimental setup, the dark-field images with high-angle illuminations are easily…

The newly installed Silmaril beam combiner at the CHARA array is designed to observe previously inaccessible faint targets, including Active Galactic Nuclei and T-Tauri Young Stellar Objects. Silmaril leverages cutting-edge optical design,…

When inverting solar spectra, image degradation effects that are present in the data are usually approximated or not considered. We develop a data reduction method that takes these issues into account and minimizes the resulting errors. By…

A Python program has been developed which fits a published detector-response model to SiPM charge spectra to characterise SiPMs. Spectra for SiPMs illuminated by low intensity pulsed light with Poisson-distributed number of photons and a…

Imaging polarimetry allows more information to be extracted from a scene than conventional intensity or colour imaging. However, a major challenge of imaging polarimetry is image degradation due to noise. This paper investigates the…

Dimensionality reduction and matrix factorization techniques are important and useful machine-learning techniques in many fields. Nonnegative matrix factorization (NMF) is particularly useful for spectral analysis and image processing in…

We present Hyper-Py, a fully restructured and extended Python implementation of HYPER (HYbrid Photometry and Extraction Routine, Traficante et al. 2015). HYPER was originally implemented in IDL, aiming to deliver robust and reproducible…

We propose a new way to correct for the non-uniformity (NU) and the noise in uncooled infrared-type images. This method works on static images, needs no registration, no camera motion and no model for the non uniformity. The proposed method…

Real-world imaging systems acquire measurements that are degraded by noise, optical aberrations, and other imperfections that make image processing for human viewing and higher-level perception tasks challenging. Conventional cameras…

We present an effective method for the matching of multimodal images. Accurate image matching is the basis of various applications, such as image registration and structure from motion. Conventional matching methods fail when handling noisy…

We present new data processing techniques that allow to correct the main instrumental effects that degrade the images obtained by ISOCAM, the camera on board the Infrared Space Observatory (ISO). Our techniques take advantage of the fact…

A Python program for calculating the metrics necessary to perform information-theory based symmetry classifications and quantifications of transmission electron diffraction spot patterns is introduced. It is the first of its kind, in that…