在一張高動態範圍的圖片之中，會同時儲存著大量的亮度及色度資訊，為了增加在傳輸以及儲存時的效率，我們必須採用適當的編碼來儲存這些資料。在這篇論文裡面我們提出了一種基於感知的高動態範圍圖片編碼方法，在這個方法裡我們採用了霍夫曼編碼，來達到類似 Ferwerda所提出的“對比對強度”曲線的階梯狀量化誤差值。另外我們更進一步的提出一個根據小波轉換後所產生的子頻資料統計圖的編碼架構，藉由分配不同的位元數給小波轉換後的低頻和高頻結果，在量化時我們可以只要用到平均5個位元就可以壓縮在人類眼睛感知範圍內的亮度資料，和以前需要10~11位元來處理亮度的方法[1]相比，我們的效率可以說是兩倍以上。此外，我們也驗證了階調映射的正確性，因為對於一個可調式視訊編碼的資料接收者而言，在低解析度模式的時候只會收到低低頻的位元流，因此無法做反小波轉換的運算。我們並且提出了一個簡單的階調映射方法來減輕小波轉換造成的影響。

A high dynamic range (HDR) image contains a vast amount of luminance and color information at the same time. In order to improve the efficiency in transmission and storage, a proper encoding method is necessary. We propose a perception-based HDR image encoding scheme using the Huffman code to achieve a quantization error curve that is below Ferwerda’s contrast versus intensity (c.v.i). With the discrete wavelet transform (DWT), we propose a sub-band histogram-based HDR image encoding scheme. By assigning different number of bits to the low band and the high band, we show that only an average of 5 bits is required to encode the luminance data under human perceptive range. This method has more than two times quantization efficiency compared with the previous result of encoding luminance data using 10~11 bits [1]. Besides, we verify the correctness of the tone mapping results from the low resolution bit stream because the receiver may only obtain the LL band data in the SVC system. We also represent a simple tone mapping way to ease the influence of DWT-tone mapping.

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