An Edge Analysis Based Blur Measure for Image Processing Applications

Abstract

本論文中提出一個新的基於邊緣分析之模糊測量標準。本項模糊測量標準是基於邊緣分析的基礎而訂立，此模糊測量標準適用於各種不同之影像處理應用。本論文所提出的方法針對所有邊緣點分析，以加權的方式結合邊緣梯度變異量資訊以及邊緣梯度強度資訊，定義出本項模糊測量標準。邊緣梯度變異量資訊描述了邊緣的寬度資訊，而邊緣梯度強度資訊則讓邊緣資訊更加的可靠。此外，加權的值並不需要人工輸入，而是直接由輸入影像的對比資訊自動決定。由實驗的結果中顯示，本論文所提出的方法在許多影像處理應用上都有良好的結果。

In this project an edge-analysis-based non-parametric-image blur measure was proposed and evaluated. This measure is based on edge analysis and is suitable for various image-processing applications. The proposed measure for any edge point is obtained by combining the standard deviation of the edge gradient magnitude profile and the value of the edge gradient magnitude, using a weighted average. The standard deviation describes the width of the edge, and its edge gradient magnitude is also included to make the blur measure more reliable. Moreover, the value of the weight is related to image contrast and can be calculated directly from the image. Experiments in the natural scenes indicate that the proposed technique can effectively describe the blurriness of images in image-processing applications.