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- An overview of multi-modal medical image fusion366
In this review, methods in the field of medical image fusion are characterized by image decomposition and image reconstruction, image fusion rules, image quality assessments, and experiments on the benchmark dataset.
- Pixel convolutional neural network for multi-focus image fusion298
Experimental results demonstrate that the proposed p-CNN is competitive with or even outperforms the state-of-the-art methods in terms of both subjective visual perception and objective evaluation metrics.
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- Union Laplacian pyramid with multiple features for medical image fusion228
Visual and statistical analyses show that the quality of fused image can be significantly improved over that of typical image quality assessment metrics in terms of structural similarity, peak-signal-to-noise ratio, standard deviation, and tone mapped image quality index metrics.
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- Detecting Generated Images by Real Images178
This work observed that the noise pattern of real images exhibits similar characteristics in the frequency domain, while the generated images are far different, and can perform image authentication by checking whether an image follows the patterns of authentic images.
- Image splicing forgery detection combining coarse to refined convolutional neural network and adaptive clustering160
The proposed C2RNet cascades a coarse convolutional neural network and a refined CNN and extracts the differences in the image properties between un-tampered and tampered regions from image patches with different scales to guarantee a stable detection performance.
- Metabolic profiling studies on the toxicological effects of realgar in rats by 1H NMR spectroscopy140
The toxicological effects of realgar after intragastrical administration were investigated over a 21 day period in male Wistar rats using metabonomic analysis of (1)H NMR spectra of urine, serum and liver tissue aqueous extracts to illustrated the high reliability of NMR-based metabonomic approach on the study of the biochemical effects induced by traditional Chinese medicine.
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- Image analysis by fractional-order orthogonal moments115
Fractional-order orthogonal moments are not only capable of region-of-interest (ROI) feature extraction but also have potential for image reconstruction and face recognition and have high noise robustness in invariant image recognition.
- Fractional discrete Tchebyshev moments and their applications in image encryption and watermarking104
A novel framework for deriving fractional order DTMs (FrDTMs) by the eigen-decomposition of kernel matrices is proposed in this paper, and some properties of the proposed FrDTMs are analyzed.
- DSAGAN: A generative adversarial network based on dual-stream attention mechanism for anatomical and functional image fusion92
A generative adversarial network based on dual-stream attention mechanism (DSAGAN) for anatomical and functional image fusion, which consumes less fusion time and achieves better objective metrics in terms of Q AG, QEN and QNIQE.
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- Brightness and contrast controllable image enhancement based on histogram specification84
Two novel histogram based image enhancement algorithms are proposed that provide the way to control the brightness and contrast of enhanced image by adjusting two parameters.
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- Lossless image compression based on integer Discrete Tchebichef Transform77
Results show that the proposed iDTT algorithm not only has higher compression ratio than iDCT method, but also is compatible with the widely used JPEG standard, and a framework of lossless image compression based on integer DTT is proposed.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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