In this paper, an algorithm based on local binary pattern (LBP) is proposed to obtain clear remote sensing images under the premise of unknown causes blurring. We find that LBP can completely record texture features images, which will not change widely due generation blur. Therefore, prior proposed, filter out pixels containing important textures in blurry image through mapping relationship. The corresponding processing methods are adopted for different types cope with challenges brought by...

With regard to inverse synthetic aperture radar (ISAR) imaging, traditional range-Doppler (RD) algorithm is inapplicable sparse aperture. Although compressive sensing (CS) can overcome this problem, the imaging resolution not high enough. When deep learning (DL) applied ISAR some problems may also occur, such as network complexity, selection of labels in training, influence noise and aperture, loss weak scattering points test. In order solve above problems, a joint fast iterative...

The remote sensing imaging environment is complex, in which many factors cause image blur. Thus, without prior knowledge, the restoration model established to obtain clear images can only rely on observed blurry images. We still build with extreme pixels but no longer traverse all pixels, such as channels. features are extracted units of patches, segmented from an and partially overlap each other. In this paper, we design a new prior, i.e., overlapped patches’ non-linear (OPNL) derived ratio...

The growing adoption of digital multimedia devices and the greater reliance on compression wireless channels for data transmission has brought renewed focus to traditional challenge evaluating image quality. Image Quality Assessment (IQA) is needed optimize bit rate, compression, or processing communication strategies these technologies. Visual representation learning enables model undertake upstream training large-scale then fine-tune downstream using fewer samples. Data annotation IQA...

A synthetic aperture radar (SAR) raw data simulator of distributed target scenes is an important tool for testing the system parameters, imaging algorithms, and so on, particularly these recently proposed novel modes. The Terrain Observation by Progressive Scans (TOPS) mode achieves wide-swath coverage overcomes major drawbacks in ScanSAR electronically steering azimuth beam along track during whole acquisition time. In this letter, a TOPS generation approach from conventional wide-beam SAR...

Synthetic Aperture Radar has been extensively used in numerous fields and can gather a wealth of information about the area interest. This large-scene data-intensive technology puts high value on automatic target recognition (ATR) which free utilizers boost efficiency. Recent advances artificial intelligence have made it possible to create deep learning-based SAR ATR that automatically identify features from massive input data. In last 6 years, intensive research conducted this area,...

Noncommunicable chronic diseases (NCDs) are a rapidly growing global public health concern, posing substantial challenges to healthcare systems. The presence of multiple (≥2) conditions (MCC) exacerbates these challenges. In this study, we constructed an integrated MCC network comprehensively evaluate the impact NCD prevalence and associated factors on patterns. We identified four distinct patterns, each with its unique set risk factors. Firstly, found that race, sedentary lifestyles,...

Accurate translational motion compensation (TMC) is the key procedure of inverse synthetic aperture radar (ISAR) imaging. Under condition sparse aperture, correlation adjacent pulses severely destroyed, which brings a few challenges to TMC and Thus, this paper proposes novel method for ISAR In technique, signal model joint phase adjustment imaging established first. Then, process designed. That is, after range alignment with improved global minimum entropy (IGME), fast orthogonal matching...

Firstly, the echo model of moving target for SAR is constructed in this paper. According to model, method detection targets based on Matched Fourier Transform discussed. Compared with bilinear time-frequency distribution algorithms, will not be affected by cross-terms when multiple exist. Moreover, because remaining Doppler frequency, spectrum strong widened, and then weak shadowed one. To solve problem, CLEAN technique domain proposed targets. The simulation results validate effectiveness method.

Magnetic resonance (MR) image reconstruction and super-resolution are two prominent techniques to restore high-quality images from undersampled or low-resolution k-space data accelerate MR imaging. Combining acquisition can further improve the acceleration factor. Existing methods often treat of separately combine them sequentially for recovery, which result in error propagation suboptimal results. In this work, we propose a novel framework joint super-resolution, aiming efficiently recovery...

Synthetic Aperture Radar has been extensively used in numerous fields and can gather a wealth of information about the area interest. This large scene data intensive technology puts high value on automatic target recognition which free utilizers boost efficiency. Recent advances artificial intelligence have made it possible to create deep learning based SAR ATR that automatically identify features from massive input data. In last 6 years, research conducted this area, however, most papers...

This study introduces a novel Blind Image Quality Assessment (BIQA) approach leveraging multi-stream spatial and channel attention model. Our method addresses challenges posed by diverse image content distortions integrating feature maps from two distinct backbones. Through mechanisms, our algorithm prioritizes regions of interest, enhancing its ability to capture crucial details. Extensive evaluations on four benchmark datasets demonstrate superior performance compared existing methods,...

Current super-resolution algorithms exhibit limitations when processing noisy remote sensing images rich in surface information, as they tend to amplify noise during the recovery of high-frequency signals. To mitigate this issue, paper presents a novel approach that incorporates concept compressed and explores problem for space cameras, particularly high-speed imaging systems. The proposed algorithm employs K-singular value decomposition (K-SVD) jointly train high- low-resolution image...

For inverse synthetic aperture radar (ISAR) imaging of targets with micromotion parts, the removal micro-Doppler (m-D) effects is key procedure. However, under condition a sparse aperture, echo pulse limited or incomplete, giving rise to difficulty eliminating m-D effects. Thus, novel algorithm proposed, which can effectively eliminate effects, as well interference introduced by noise and in ISAR image main body. The proposed mainly includes two processing steps. First, combined cut-off...