Edge enhancement

About: Edge enhancement is a research topic. Over the lifetime, 2324 publications have been published within this topic receiving 30962 citations.

Super-Resolution Image Reconstruction Using Wavelet Based Patch and Discrete Wavelet Transform

Abstract: This paper proposes a novel method that combines the discrete wavelet transform (DWT) and example-based technique to reconstruct a high-resolution from a low-resolution image. Although previous interpolation- and example-based methods consider the reconstruction adaptive to edge directions, they still have a problem with aliasing and blurring effects around edges. In order to address these problems, in this paper, we utilize the frequency sub-bands of the DWT that has the feature of lossless compression. Our proposed method first extracts the frequency sub-bands (Low-Low, Low-High, High-Low, High-High) from an input low-resolution image by the DWT, and then the low-resolution image is inserted into the Low-Low sub-band. Since information in high-frequency sub-bands (Low-High, High-Low, and High-High) might be lost in the low-resolution image, they are reconstructed or estimated by using example-based method from image patch database. After that, we make a high-resolution image by performing the inverse DWT of reconstructed frequency sub-bands. In experimental results, we can show that the proposed method outperforms previous approaches in terms of edge enhancement, reduced aliasing effects, and reduced blurring effects.

Perceptually relevant ringing region detection method

Abstract: A novel approach towards automatic detection of perceived ringing regions is presented. The algorithm takes into account both the physical structure and the human visual perception of the ringing artifacts. All perceived ringing regions are explicitly captured by means of a newly proposed edge detector, followed by an efficient analysis of ringing visibility around each detected edge segment. Determining visibility is based on luminance masking and texture masking as typical for the human visual system. The proposed detection method is validated by comparing its performance with the ringing regions resulting from a psychovisual experiment.

Image Enhancement and Its Various Techniques

Abstract: Image enhancement is the task of applying certain alterations to an input image like as to obtain a more visually pleasing image. The alteration usually requires interpretation and feedback from a human evaluator of the output resulting image. Image enhancement is to improve the image quality so that the resultant image is better than the original image for a specific application or set of objectives. Enhancement techniques such as alpha rooting operate on the transform domain. The transform domain enables operation on the frequency content of the image, and therefore high frequency content such as edges and other subtle information can easily be enhanced. However, these techniques bring about tonal changes in the images and can also generate unwanted artifacts in many cases, as it is not possible to enhance all parts of the image in balanced manner.

Depth image-based rendering with low resolution depth

Abstract: This paper proposes a new approach for depth image-based rendering (DIBR) with low resolution depth using the 3D propagation algorithm. Our novel depth edge enhancement method efficiently corrects and sharpens the depth edges in the propagated depth image using available high resolution color information. Experimental results show that only with 4% depth information kept for low resolution depth image, the proposed method can provide comparable rendering quality to that of the high resolution case. Furthermore, the proposed work is developed to match the fine-grain parallelism of general-purpose graphics processing units (GPGPUs) and hence can be accelerated to nearly real-time operations in low cost DIBR systems.