Neural-network-based image resolution enhancement from a multiple of low-resolution images

2003 ◽  
Author(s):  
Ezzatollah Salari ◽  
Shuangteng Zhang
Keyword(s):  
Neural Network ◽  
Resolution Enhancement ◽  
Image Resolution ◽  
Low Resolution ◽  
Low Resolution Images

scholarly journals Intelligent Image Synthesis for Accurate Retinal Diagnosis

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 767 ◽  
Author(s):  
Dong-Gun Lee ◽  
Yonghun Jang ◽  
Yeong-Seok Seo
Keyword(s):  
Image Data ◽  
Image Synthesis ◽  
Image Resolution ◽  
Retinal Images ◽  
Synthetic Approach ◽  
Test Image ◽  
Low Resolution ◽  
Medical Field ◽  
Retinal Examination ◽  
Low Resolution Images

Ophthalmology is a core medical field that is of interest to many. Retinal examination is a commonly performed diagnostic procedure that can be used to inspect the interior of the eye and screen for any pathological symptoms. Although various types of eye examinations exist, there are many cases where it is difficult to identify the retinal condition of the patient accurately because the test image resolution is very low because of the utilization of simple methods. In this paper, we propose an image synthetic approach that reconstructs the vessel image based on past retinal image data using the multilayer perceptron concept with artificial neural networks. The approach proposed in this study can convert vessel images to vessel-centered images with clearer identification, even for low-resolution retinal images. To verify the proposed approach, we determined whether high-resolution vessel images could be extracted from low-resolution images through a statistical analysis using high- and low-resolution images extracted from the same patient.

OBJECT QUALITY ENHANCEMENT OF MULTI-FRAME LOW-RESOLUTION VIDEO

2015 ◽  
Vol 77 (22) ◽  
Author(s):  
Siti Aisyah ◽  
Fitri Arnia
Keyword(s):  
Nearest Neighbor ◽  
Resolution Enhancement ◽  
Subjective Assessment ◽  
Object Identification ◽  
Image Resolution ◽  
Frame Rate ◽  
Low Resolution ◽  
Video Frames ◽  
Enhancement Method ◽  
Good Quality Image

A good quality image is required in various applications such as object identification and authentication. This research presents the performance of image resolution enhancement method, in which the low-resolution image originated from low-resolution CCTV video. The enhancement method is initialized by averaging video frames and continued by interpolating the resulted images using the existing interpolation techniques, namely bilinear, bi-cubic, nearest neighbor and spleen. Frame rate of 15 and 25 frames per second (fps) has been applied to the testing video. The result shows that the differences of frame rate and number of the averaged frame would affect image quality. Subjective assessment of respondents of MOS above 3 has been obtained by increasing the frame rate and the number of averaging frames.  

scholarly journals Adaptive Cycle Spinning Cellular Neural Network for Image Resolution Enhancement

2014 ◽  
Vol 18 (4) ◽  
pp. 173-176
Author(s):  
Kei Chiba ◽  
Tsuyoshi Otake ◽  
Hisashi Aomori ◽  
Nobuaki Takahashi ◽  
Mamoru Tanaka
Keyword(s):  
Neural Network ◽  
Resolution Enhancement ◽  
Cellular Neural Network ◽  
Image Resolution ◽  
Adaptive Cycle ◽  
Cycle Spinning
Sign in / Sign up

Export Citation Format

Share Document