為了節省硬體的成本，現在的數位相機大多採用單一感光元件並配合RGB色彩濾波陣列來捕捉真實世界的場景。由於拍攝到的影像中，每一個像素只包含紅、綠、藍其中一種主色，因此這類的影像我們稱之為馬賽克影像。由於全彩影像是人們較為接受的，將馬賽克影像轉換成全彩影像是必要的。本論文提出一套結合Huber損失函數的殘量內插解馬賽克演算法。所提方法中，利用Huber損失函數來壓抑離群值對線性回歸的結果。同時也提出利用兩種遮罩的結合方法，來取得較好的影像品質。我們實作三種代表性的測試影像，實驗結果顯示本論文所提出的方法有較好的影像品質。

To save hardware cost, most modern digital cameras employ the single-sensor
technology together with the red-green-blue (RGB) color filter array (CFA) structure to capture real-world scenes. Since each pixel in the captured image is only composed of one primary color, such an image is usually referred to as the mosaic image. For the purpose of visual display, it is necessary to convert the captured mosaic image into the full-color RGB image. In this thesis, we propose a novel residual interpolation for image demosaicking associated with Huber-loss function. In the proposed method, we use Huber-loss function to decrease the effect of outliers which affect the result of linear regression. Besides, we also use two different sizes of mask to fuse the result of tentative demosaicked image. Based on 3 image datasets, experimental results show that the demosaicked image generated by the proposed demosaicking method has better quality in terms of visual signal-to-noise ratio (CPSNR) and demonstrates less
color artifact when compared with Tanaka et al.’s methods.

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