Intel RealsenseD435 color图与depth图的两种对齐（align）方式
對齊原理
The term “alignment” w.r.t SDK denotes a synthetic image generation with the help of depth map. In the process a new image is created using triangulation method comprising of 2D=>3D=>2D transformations.
The transformation is akin to a ray tracing - each pixel is first “fired” from 2D to 3D space, and then projected into the 2D plane of another sensor.
So by definition the aligned data is generated from depth in conjunction with color/ir data, hence the areas with no depth data coverage result in “holes” in the generated image.
The above serves a specific purpose - allowing 1:1 mapping of depth to color and vice versa. So when a user selects RGB pixel of interest then the SDK will be able to provide the corresponding Depth deterministically with no false positives.
This is a critical feature in scenarios where the depth is essentially used as a validation filter for other sensors - collision avoidance, segmentation, object recognition.
While using sheer 2D image manipulations would similarly allow to recalculate an image from a different point of view, it would also introduce fundamental flaws - preserve the pixels for which there is no corresponding depth data, and also introduce artifacts due to occlusion and different perspective, which would undermine the declared purpose.
Eventually there are more than one way to “align” images, depending of the use-case requirements. And the above explanation highlights the specific advantage (and also the utility) of the method implemented by the SDK.
SDK中的“對齊”一詞表示借助深度圖生成的合成圖像。在此過程中，將使用由2D => 3D => 2D轉換組成的三角測量方法來創建新圖像。
轉換類似于ray tracing－每個像素首先從2D空間“發射”到3D空間，然后投影到另一個傳感器的2D平面中。
因此，根據定義，對齊的數據是結合顏色/ ir數據從深度生成的，因此沒有深度數據覆蓋的區域會在生成的圖像中產生“孔”。
上面的內容用于特定目的-
允許將深度與顏色進行1：1映射，反之亦然。因此，當用戶選擇感興趣的RGB像素時，SDK將能夠確定性地提供相應的深度，而不會產生誤報。
這在深度實際上用作其他傳感器的驗證過濾器（避免碰撞，分割，物體識別）的情況下是至關重要的功能。
雖然使用純粹的2D圖像處理可以類似地從不同的角度重新計算圖像，但它也會帶來基本的缺陷-保留沒有相應深度數據的像素，并且還會由于遮擋和視角不同而引入偽像，這會破壞宣布的目的。
最終，取決于用例需求，有不止一種“對齊”圖像的方法。上面的說明著重介紹了由SDK實現的方法的特定優勢（以及實用程序）。
參考文章：Align to Depth produces lossy color image #5030
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