A Regularized Robust Super-resolution Approach Foraliased Images and Low Resolution Videos
نویسندگان
چکیده
This paper presents a hybrid approach for images and video super-resolution. We have proposed the approach for enhancing the resolution of images and low resolution, under sampled videos. We exploited the shift and motion based robust super-resolution (SR)algorithm [1] and the diffusion image regularization method proposed in [2] to obtain the alias free and jerk free smooth SR image.We presented a framework for obtaining super-resolution video thatis robust,even in the presence of fast changing video frames. Wecompare our hybrid approach framework’s simulation results with different resolution enhancement techniques i.e. Robust Super-resolution, IBP and Interpolation methods reported in the literature. This approach shows good results in term of different quality parameters.
منابع مشابه
Robust Fuzzy Content Based Regularization Technique in Super Resolution Imaging
Super-resolution (SR) aims to overcome the ill-posed conditions of image acquisition. SR facilitates scene recognition from low-resolution image(s). Generally assumes that high and low resolution images share similar intrinsic geometries. Various approaches have tried to aggregate the informative details of multiple low-resolution images into a high-resolution one. In this paper, we present a n...
متن کاملSuper-resolution of Defocus Blurred Images
Super-resolution is a process that combines information from some low-resolution images in order to produce an image with higher resolution. In most of the previous related work, the blurriness that is associated with low resolution images is assumed to be due to the integral effect of the acquisition device’s image sensor. However, in practice there are other sources of blurriness as well, inc...
متن کاملA Deep Model for Super-resolution Enhancement from a Single Image
This study presents a method to reconstruct a high-resolution image using a deep convolution neural network. We propose a deep model, entitled Deep Block Super Resolution (DBSR), by fusing the output features of a deep convolutional network and a shallow convolutional network. In this way, our model benefits from high frequency and low frequency features extracted from deep and shallow networks...
متن کاملImproving Super-resolution Techniques via Employing Blurriness Information of the Image
Super-resolution (SR) is a technique that produces a high resolution (HR) image via employing a number of low resolution (LR) images from the same scene. One of the degradations that attenuates performance of the SR is the blurriness of the input LR images. In many previous works in the SR, the blurriness of the LR images is assumed to be due to the integral effect of the image sensor of the im...
متن کاملPseudo Zernike Moment-based Multi-frame Super Resolution
The goal of multi-frame Super Resolution (SR) is to fuse multiple Low Resolution (LR) images to produce one High Resolution (HR) image. The major challenge of classic SR approaches is accurate motion estimation between the frames. To handle this challenge, fuzzy motion estimation method has been proposed that replaces value of each pixel using the weighted averaging all its neighboring pixels i...
متن کامل