An alternative cascaded human-visual-system (HVS) based mechanism has been applied on high-dynamic-range image reproduction. It obtains appreciated results compared with several previous strategies. The proposed mechanism consists of three aspects. The first stage is the notch filtering on frequency domain, referring to the adaptive mechanism of HVS. Based on the logarithm transformation and learning method, the physical halo-effect was also eliminated in some degrees. The second is the center-surround spatial filtering, which enhances the edges with higher visual contrast sensitivity in spatial frequency. It aims to distinct objects based on the TVI (transition versus intensity) function. The last one is pixel-wise detail modulation for enhancing the photography sensation in virtue of flatting histogram. The experimental results also show out the pleasing details in images. This multiple-stages approach is appreciated for enhancing images with low-contrast edges or dimming-room pictures, and it also helpful to treat the low-visual-quality images in surveillance or health-care monitoring systems. 本研究提出一種新的區域影像強化方法，可以將高動態範圍影影像成功的作強化與影像重製。此方法乃以人類視覺系統運作的可適應性為基礎，藉由頻域與空間域的濾波器來達成此種高難度的影像重製處理。此方法的結果將實現在許多通用的高動態範圍測試影像上，也獲得相當滿意的結果；並與5種常用的方法作比較，更可顯出本方法在視覺感受上的差異性。此方法大致上可分為三個步驟。第一為運用notch 濾波器在頻域上做處理。我們利用對數的轉換與標準影像的參數學習方式可以找出對應的濾波器參數，並且將halo-effect 降到最低。其次，利用視覺對對空間域上邊(edge)的敏感程度不同，利用TVI函數對視覺敏感度的參數將空間域center-surround 濾波器的參數定出。藉此強化視覺辨識最敏感的邊而銷弱不敏感的邊，大幅提升影像品質。最後，對於局部對整理的灰度分部做調整，此意在強化像素間的對比 (pixel-wise)。在實驗中我們也可以看到許多細節部份也可被清楚的呈現出來。 此種多重視覺感知的處理方式不僅可以運用在高飽和或低對比的影像處理，尤 其它的多階效果可以用來處理許多在室內拍攝的影像，如一般的監視系統甚至老人照護的觀察系統。
