Efficient deinterlacing method using simple edge slope tracing

Abstract

Abstract. This paper presents a low-complexity interpolation method that minimizes image quality losses at edges, which are easily perceivable by the human eye. Deinterlacing, which converts an interlaced video into a progressive video, is a problem in image interpolation that doubles the number of vertical lines. Applying averaging, or any linear algorithm, achieves time-efficient deinterlacing but produces artifacts. However, applying other complex methods tends to reduce unwanted artifacts but at the cost of high computation time. The proposed deinterlacing scheme is based on an algorithm called "edge slope tracing" which simply predicts the slope on the basis of information on adjacent slopes. Predicted slopes are used to perform deinterlacing in slope-based line averaging. The simulation results show that this scheme provides better results and reduces complexity compared to conventional state-of-the-art algorithms. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Storage Optimization using Adaptive Thresholding Motion Detection

“…INTRODUCTION Image and video processing involves the transmission and storage of large data volumes in the form of frames and images. Several researchers [1][2][3] worked on reducing bandwidth requirements, whereas others [4] worked on optimizing storage utilization. In today's modern world, a huge amount of data is being generated [5], therefore, extracting the required information from large data volumes is a difficult task, while the storage of large data volumes is an issue [6].…”

Review on Deinterlacing Algorithms

“…Leading to burdened calculations and low efficiency due to many correlation calculations involved in interpolating. EST technique [3] is used to interpolate along these gently sloped edge regions of the image. A lower complexity algorithm based on information on slope of previous pixels is taken into consideration to estimate slope by predicting slope for the current pixel.…”

Efficient Edge-Based Image Interpolation Method Using Neighboring Slope Information

“…Table 2 shows a comparison of the execution time for all five algorithms when they were applied to the test images given in [19], [20]. The execution time for bicubic is far less compared to NEDI and ICBI.…”

“…EEST predicts the slope of the current pixel on the basis of the information obtained from the slope of the adjacent pixel. EEST is based on improvement of EST that was first introduced for deinterlacing [19], [20]. It has some serious problems with interpolation due to limited slope candidates and using of 1 × 3 window based artifacts correction techniques that depends on results of line averaging which causes in blurring along the edges when used for interpolation.…”