考慮感知程度之影像品質評估

Image quality assessment based on perceptual quality

徐詩媛(Shih-Yuan Hsu)

指導教授 ： 郭天穎 ； 陳建中

國立臺北科技大學/電資學院/電機工程系研究所/碩士(2013年)

摘要

影像品質評估主要在評估兩張影像的視覺差異程度，一般演算法會在影像評估方法中加入人類視覺系統(Human visual system，HVS)的特性，讓影像評估的結果更符合人眼察覺到的影像品質。本文去改善了目前大多數的演算法，不只專注於研究更有效的比較兩張影像局部的資訊，進而著重人眼對於影像不同內容和不同失真程度的敏感度不同。
本文提出基於VIF的評估方法作改進，首先使用Haar小波轉換和對數-賈伯濾波器(Log-Gabor filter)，擷取影像上人眼較敏感的特徵；並利用運算複雜度較低的Laplacian filter偵測影像的物件區域，再加入SSIM計算失真區域，讓影像評估同時著重於包含物件和失真較嚴重的視覺敏感區域。而在對數-賈伯濾波器擷取人眼敏感的特徵之前時使用了對比度敏感函數(Contrast sensitivity function，CSF)特性調整頻帶響應何給予權重。由於VIF本身著重於信息量的比較，無法有效地評估亮度(Luminance)失真，所以我們並在計算影像信息量的時候，亦將SSIM其中的亮度失真考慮進去，以彌補VIF對於亮度失真的缺失。
經影像資料庫測試結果發現，本文所提出的影像評估的效能和效率超越了文獻常見的演算法。

關鍵字

影像品質評估 ； 對數-賈伯濾波器 ； 頻譜冗餘 ； 結構相似性 ； 視覺信號保真度 ； 視覺敏感特性 ； 對比度敏感函數(CSF)

並列摘要

Image quality assessment is to measure the visual difference between two images. In order to make evaluation result in line with the visual quality perceived by the human, it is necessary to make use of the characteristic of the human visual system (HVS) into image quality assessment methods. Most of the literature works focus on how to more effectively compare two images of local information, but ignore the fact that they should have unequal sum-up weighting to the total, as the human vision has different sensitivity in regions with different contents and distortion.
This work proposes an image assessment methods based on VIF. At the first, we extract the features of visual sensitivity in images with the Haar wavelet transform and log-Gabor filter, and detect the salient object region with the Laplacian filter, and calculate the distortion region with SSIM. For log-Gabor filter, we apply weighting to the log-Gabor frequency band based on the contrast sensitivity function (CSF). Since VIF assessment is based on the information comparison and not effective in luminance distortion, we take into account the luminance component of SSIM in the image information calculation, to compensate for the weakness of VIF in brightness distortion.
The experimental results on image database show that our overall performance and efficiency outperforms the general image quality assessment methods.

並列關鍵字

Image quality assessment ； log-Gabor filter ； structural similarity (SSIM) ； visual information fidelity (VIF) ； visual sensitivity ； contrast sensitivity function

參考文獻

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