隨著電子技術的日新月異，在影像擷取技術的發展上，無論是攝影機或是照相機都走向數位化趨勢。在拍攝目標的顏色上，常會因為投射光源的不同而改變；人類的眼睛會自動隨著光源改變而作顏色的修正，但是目前最常使用的電子感光元件--電荷耦合裝置，無法具備如人眼的校正功能。 本論文採用Lam的自動白平衡演算法，其結合Gray World Assumption 和Perfect Reflector Assumption 演算法[1]。Lam演算法的執行步驟分為三個階段，每一個階段做軟硬體設計與分析；對於實驗結果我們分別統計執行時間、硬體資源Slices和硬體資源 DSP48s等三個因素。在本論文中，使用Objective Function來評估系統效能與硬體資源，求得兩者平衡之軟硬體分割情形。同時，我們使用Xilinx公司發展之嵌入式處理器MicroBlaze並配合一個浮點運算器，處理軟體部分的演算法；硬體的部分則以IP-Based方式設計之硬體處理。藉由可程式化單晶片之架構優勢，可節省個人電腦的記憶體及中央處理器資源，亦擁有易於修改及擴充功能的設計彈性。

As electronic techniques is continuous improved rapidly cameras or video camcorders used for image retrieval technology and development become digitalized. The color of the photographs would look very different due to differences in light projection illumination when we take a picture. Human eyes are able to automatically adjust the color when the illuminations of the light source vary. However, the most frequently used image sensor, charge coupled device, CCD device can not correct the color as human eyes. This paper presents a hardware-software co-design method based on Lam's automatic white balance algorithm, which combines gray world assumption and perfect reflector assumption algorithms [1]. The execution steps of Lam's algorithm were divided into three stages. The hardware-software co-design and analysis for each stage was realized. Three factors including processing time, slices and DSP48s of hardware resources were used to formulate a Objective Function, which was employed to evaluate the system performance and hardware resource cost. Experimental results shows suitable partitions of hardware-software co-designs were achieved. An embedded processor, MicroBlaze developed by Xilinx and a floating point processor were used to deal with the software part of the algorithm. The hardware part of the algorithm was implemented using an IP-based method. It is able to reduce the memory and CPU resources of the PC as well as to have the properties of easy modification and function expansion by using such system on a programmable chip architecture.