Extended intelligent edge-based line average with its implementation and test method
Yu-Lin Chang, Shyh-Feng Lin, Liang‐Gee Chen · 2004
In this paper, an extended intelligent edge-based line average-EIELA is proposed. The EIELA could be used in intra-field de-interlacing to remove the jagged edges and the blurring effect of the bilinear interpolation or the traditional algorithms. The EIELA could change its performance dynamically according to the user's requirement. The proposed method can achieve the highest image quality of the traditional ELA if all the taps in the module are enabled, and it also possesses the ability to reduce the taps usage and instruction counts through the turn-off of some calculating sub-modules. The results and VLSI implementation show the proposed method achieve high image quality and low hardware complexity.