在數十年來，電腦視覺與圖形辨識已有長足的進步，這些研究發展出多種的辨識方法，其中許多的辨識模型可以達到相當程度的辨識率，這些方法主要都是想達到人類視覺的辨識結果，一個圖形通常會對應到唯一的答案，但是有時候人類對於某些簡單的圖形不見得會有相同的一種答案，關於這種現象我們認為是由於觀察圖片時，人眼對圖片的取樣不同，再經過大腦的理解後，就得到不同的解釋結果。
我們借用量子力學中的光子共振概念與隨機取樣來建立一套像素共振計算法作為解釋這種想法的理論基礎，並且運用蒙地卡羅法則來進行模擬；當給予圖片不同的亂數取樣就可以得到不同的辨識結果，我們稱這為圖形的多重解釋。將像素共振計算法套用在可辨識成兩種結果的字母與中文字，結果可以看出共振計算法中，給予不同的條件會有不同的圖形顯示出來。
在本篇論文裡，我們也將圖形的像素共振與多重解釋延伸到彩色影像與色盲測試圖上，藉由不同條件的共振測試，可以得到不同的共振結果。此外，在CIE xyY色彩空間上來取樣顏色，以用來合成來我們的色盲測試圖，並且利用提出像素共振計算法分析色盲測試圖，也用色盲模擬器來檢驗色盲人觀看我們合成的色盲圖效果，再由模擬色盲觀看色盲測試圖的視覺角度以顯示圖形多重解釋的概念。

For these years, computer vision has made great progress in pattern recognition. Many recognition models have been proposed and some of them achieved fairly good recognition rate. The ultimate goal of these methods is mainly to realize the recognition capability of human vision. Usually, for an image containing a simple object, the human vision will associate only one interpretation of the object in response to such image. However, there are cases where one viewer or different viewers may not always respond with the same answer when viewing the same simple figure. We call this multi-interpretations. About this phenomenon, we propose an explanation that it is because the viewer(s) might have different sensing criterion when viewing an image. After the differently sensed result is received and processed by the brain, different response pattern might be produced, thus different interpretations to the same image occur.
To support our idea of explaining the aforementioned phenomena, we develop a pixel resonance concept based on random sampling and the photon cluster resonance concept of quantum mechanics to model different sensing criterion effect. A Monte Carlo method is applied in our pixel resonance simulation to illustrate the proposed multi-interpretations concept. If a given image is randomly sampled by different sampling energy, different resonance results might be obtained, thus multi-interpretations.
We then extend the pixel resonance and multi-interpretations concept to color image and color blindness tests. Using different resonance conditions, the different resonance images are obtained. In addition, we further explain the concept about multi-interpretations by simulating color blind vision of color blindness tests.

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