Greetings, fellow Nawala! May you always be in good health.
This is the IAES Nawala of the Institute of Advanced Engineering and Science. Today we will share some news about image restoration. Image restoration refers to the process of improving the quality and appearance of digital images that have been degraded or damaged by noise, blurring, compression artifacts, or other forms of distortion. Image restoration techniques aim to restore the original image as closely as possible and reduce the effects of degradation. Altaie (2021) conducted research related to image restoration using guided filtering and inverse filters. A more complete description of the research can be seen on the following page:
Restoration for blurred noisy images based on guided filtering and inverse filter
Rusul H. Altaie
The development of complex life leads into a need using images in several fields, because these images degraded during capturing the image from mobiles, cameras and persons who do not have sufficient experience in capturing images. It was important using techniques differently to improve images and human perception as image enhancement and image restoration etc. In this paper, restoration noisy blurred images by guided filter and inverse filtering can be used for enhancing images from different types of degradation was proposed. In the color images denoising process, it was very significant for improving the edge and texture information. Eliminating noise can be enhanced by the image quality. In this article, at first, The color images were taken. Then, random noise and blur were added to the images. Then, the noisy blurred image passed to the guided filtering to get on denoised image. Finally, an inverse filter applied to the blurred image by convolution an image with a mask and getting on the enhanced image. The results of this research illustrated good outcomes compared with other methods for removing noise and blur based on PSNR measure. Also, it enhanced the image and retained the edge details in the denoising process. PSNR and SSIM measures were more sensitive to Gaussian noise than blur.
Computer vision is a multidisciplinary field of artificial intelligence (AI) and computer science that focuses on the ability of computers or machines to interpret and understand visual objects such as images and videos. Razzok et al. (2022) utilized image restoration technology to improve the results of computer vision analysis. This research focuses on pedestrian image detection. The results of their research can be accessed on the following page:
Mohammed Razzok, Abdelmajid Badri, Ilham El Mourabit, Yassine Ruichek, Aïcha Sahel
Pedestrian detection has so far achieved great success in normal illumination, while pedestrians captured in extreme weather are often ignored. This paper investigates the importance of studying the effects of weather conditions on the recognition task, such as blurring and low contrast. Many image restoration techniques have recently been proposed, but are still insufficient to remove weather effects from images. We present our strong new pedestrian recognition system against climate situations, which is based on locating contours cues by applying multiple edge filters and extracting multiple features from images such as census transform (CT), modified census transform (MCT), and local gradient pattern (LGP) without performing any image restoration algorithm. The next stage involves finding the most discriminative characteristics using feature selection (FS) techniques. Finally, we use the final feature vector as an input to a radial basis function-based support vector machine classifier (RbfSVM) for pedestrian recognition. Experiments are performed on the daimler pedestrian classification benchmark dataset. Results show that the area under the curve (AUC) and the detection rate of our model are less affected by weather conditions compared to other common models like histogram of oriented gradients (HOG) and gabor filter bank (GFB) detectors.
Some of the articles above are a small part of the research on image restoration technology. To get more information, readers can visit the International Journal of Electrical and Computer Engineering (IJECE) and IAES International Journal of Artificial Intelligence (IJ-AI) pages for FREE via the following links: https://ijece.iaescore.com/ and https://ijai.iaescore.com/.
by: I. Busthomi
editor: S. D. Cahyo