The fidelity of the trajectories obtained from video-based particle tracking determines the success of a variety of biophysical techniques, including in situ single cell particle tracking and in vitro motility assays. However, the image acquisition process is complicated by system noise, which causes positioning error in the trajectories derived from image analysis. Here, we explore the possibi...

The use of low-dose computed tomography (LDCT) in medical practice can effectively reduce the radiation risk patients, but it may increase noise and artefacts, which compromise diagnostic information. methods based on deep learning improve image quality, most them a training set aligned pairs, are difficult to obtain practice. In order solve this problem, basis Wasserstein generative adversaria...

A recently developed blind deblurring algorithm based on the edge-to-noise ratio has been applied to improve the quality of spiral CT images. Since the discrepancy measure used to quantify the edge and noise effects is not symmetric, there are several ways to formulate the edge-to-noise ratio. This article is to investigate the performance of those ratios with phantom and patient data. In the p...

Low bit-rate image coding brings about obvious degradation to the compressed images, among which distortions at edges are particular objectionable. In this paper, a model-based edge reconstruction algorithm is proposed for wavelet-based image coding at low bitrate. Our approach applies a general model to represent varieties of edges existing in an image. Based on this model, the problem of edge...

A challenge in photoacoustic tomography (PAT) brain imaging is to compensate for aberrations in the measured photoacoustic data due to their propagation through the skull. By use of information regarding the skull morphology and composition obtained from adjunct x-ray computed tomography image data, we developed a subject-specific imaging model that accounts for such aberrations. A time-reversa...

In many image coding applications such as web browsing, image database, and telemedicine, it is useful to reconstruct only a region of interest (ROI) before the rest of the image is reconstructed. In this paper, an ROI coding functionality is incorporated with the set partitioning in hierarchical trees (SPMT) algorithm [ 13. By emphasizing the ROI coefficients, they are coded with higher fideli...

In this paper, we propose a robust image super resolution algorithm, which aims to maximize the overall visual quality of super resolution results. We consider a good super resolution algorithm to be fidelity preserving, image detail enhancing and smooth. Accordingly, we define perception-based measures for these visual qualities. Based on these quality measures, we formulate image super resolu...

In this paper, we propose a robust image super-resolution algorithm, which aims to maximize the overall visual quality of super-resolution results. We consider a good super-resolution algorithm to be fidelity preserving, image detail enhancing and smooth. Accordingly, we define perception-based measures for these visual qualities. Based on these quality measures, we formulate image super-resolu...

This book chapter presents an introduction to image spectrometers with as example their application to the scanning of fine-art paintings. First of all, the technological aspects necessary to understand a camera as a measuring tool are presented. Thus, CFA-based cameras, Foveon-X, multi-sensors, sequential acquisition systems, and dispersing devices are introduced. Then, the simplest mathematic...

In this work, we investigate the nearly lossless image compression technique, which provides a better compression ratio than purely loss-less compression schemes and has a better reconstructed image quality than lossy ones. In particular, we introduce a new idea called the soft decision quantization and integrate it with the binary arithmetic QM coder. The superior performance of the developed ...