After the high-frequency clipping, rather than processing separately on each level, we transform the filtered images back to their original resolutions for ...

In this paper, we examine the problem of selecting optimal levels in the multi-resolution analysis to preprocess the image for perceptual quality assessment.

There- fore, in this paper, we try to directly remove part of image details using adaptive high-frequency clipping in wavelet sub- bands. The AHC model filtered ...

This paper proposed a wavelet transform based adaptive high-frequency clipping (AHC) model to approximate the effective visual information that enters the ...

In this paper, we examine the problem of selecting optimal levels in the multi-resolution analysis to preprocess the image for perceptual quality assessment.

Sep 12, 2024 · This framework aims to fast adapt the powerful visual-language pre-trained model, CLIP, to downstream IQA tasks, significantly improving ...

This paper proposed a wavelet transform based adaptive high-frequency clipping (AHC) model to approximate the effective visual information that enters the ...

You use different adaptive strategies: frequency clipping for image classification vs including frequency magnitude in the loss for object detection.

This paper, named as Selective Apex Adaptive Histogram Equalization (SLAAHE), proposes an effective and efficient contrast enhancement algorithm.

In fact, our OSS model runs by performing a pre-filtering based on adaptive high-frequency clipping in the DWT domain, and then resizing the filtered images to ...