Related papers: Compressed ghost edge imaging
A scenario of ghost imaging with hybrid transform approach is proposed by integrating Hadamard, discrete cosine, and Haar matrices. The measurement matrix is formed by the Kronecker product of the two different transform matrices. The image…
Guided image filter is a well-known local filter in image processing. However, the presence of halo artifacts is a common issue associated with this type of filter. This paper proposes an algorithm that utilizes gradient information to…
Both ghost imaging (GI) and ghost imaging via compressive sampling (GICS) can nonlocally image an object. We report the influence of spatial transverse coherence property of a thermal source on GI and GICS and show that, using the same…
Conventional computational ghost imaging (CGI) uses light carrying a sequence of patterns with uniform-resolution to illuminate the object, then performs correlation calculation based on the light intensity value reflected by the target and…
Compressive sensing (CS) works to acquire measurements at sub-Nyquist rate and recover the scene images. Existing CS methods always recover the scene images in pixel level. This causes the smoothness of recovered images and lack of…
Context-based detection methods such as DetectGPT achieve strong generalization in identifying AI-generated text by evaluating content compatibility with a model's learned distribution. In contrast, existing image detectors rely on…
In certain applications or wavelength regimes, essential optical components for imaging systems are either unavailable or challenging to fabricate. To address this, we propose an optics-free classical ghost imaging (GI) scheme utilizing…
Edge Detection Methods Based on Differential Phase Congruency of Monogenic Image Abstract: Edge detection has been widely used in medical image processing and automatic diagnosis. Some novel edge detection algorithms,based on the monogenic…
Edge detection is a critical component of many vision systems, including object detectors and image segmentation algorithms. Patches of edges exhibit well-known forms of local structure, such as straight lines or T-junctions. In this paper…
As one of important analysis tools, microscopes with high spatial resolution are indispensable for scientific research and medical diagnosis, and much attention is always focused on the improvement of resolution. Over the past decade, a…
Used in the paper is an overcomplete piecewise-polynomial image model incorporating sparsity. The paper shows that using such a model, the edges in the image can be resolved robustly with respect to noise. Two variants of the proposed…
Ghost imaging is a method to nonlocally image an object by transmitting pairs of entangled photons through the object and a reference optical system respectively. We present a theoretical analysis of the quantum noise in this imaging…
Hyperspectral image (HSI) clustering groups pixels into clusters without labeled data, which is an important yet challenging task. For large-scale HSIs, most methods rely on superpixel segmentation and perform superpixel-level clustering…
This paper focuses on camouflaged object detection (COD), which is a task to detect objects hidden in the background. Most of the current COD models aim to highlight the target object directly while outputting ambiguous camouflaged…
Astronomical images are often plagued by unwanted artifacts that arise from a number of sources including imperfect optics, faulty image sensors, cosmic ray hits, and even airplanes and artificial satellites. Spurious reflections (known as…
Snapshot compressed sensing (CS) refers to compressive imaging systems in which multiple frames are mapped into a single measurement frame. Each pixel in the acquired frame is a noisy linear mapping of the corresponding pixels in the frames…
This paper presents an improved edge detection algorithm for facial and remotely sensed images using vector order statistics. The developed algorithm processes colored images directly without been converted to gray scale. A number of the…
A spectral camera based on ghost imaging via sparsity constraints (GISC) acquires a spectral data-cube (x; y; {\lambda}) through a single exposure. The noise immunity of the system is one of the important factors affecting the quality of…
Remote sensing images are frequently degraded by adverse weather conditions, particularly clouds and haze, which severely impair downstream applications. Existing restoration methods typically rely on computationally heavy architectures or…
Ghost imaging radar is a new system of gaze imaging radar with high detection sensitivity, super-resolution and better anti-interference performance, but the relative motion between the radar system and the target will make the target…