Image masking refers to the process of eliminating the background of an image which has some sort of defect ranging from blurry or hairy edges. Image masking can be done in either of two ways. Firstly, by using an image as a mask. The other form is using a region of interest as the mask. The reguions of interest for each mask can be used to describe the mask. In the regions of interest toolkit, the masking can be done separately in a slice by slice basis. The simplest way of defining image masking is a way of applying something to a very specific portion of an image. There are two primary forms of masks. They are layer masks and clipping masks. A layer mask is something that you add to a layer to control the transparency. When a mask is added to a layer, it converts the entire thing with an invisible gray canvas. On that invisible canvas, you can paint any color you like. Clipping layer is also somewhat similar to layer masks where the only difference is they use one layer to sort out the transparency of that particular area.
Once learned about the masking tool, the learner may think that he can do all of this work using an eraser. But in reality, the eraser tool is a destructive one. Masking techniques range from absolutely simple from extremely complex. The image masking tools takes in the input, produces a new image by making a copy of the original with a pixel intensity value set to zero. Often masking is used to apply varying levels of transparency to an image. A mask is formed of a grayscale channel which is described as the alpha channel which is used as an overlay to the original image. The dark areas of the mask are the ones which are most protected and the white areas are the one most unprotected. Masks are put to used in different way depending on the application used but the basic concepts are the same. Essentially, a mask is a grayscale bitmap image. A mask does not have to be a separate image. Most applications allow us to illustrate a mask directly into our images. Trasparency is indicated through a checkerboard pattern. Adding to a mask creates white, subtracting from a mask creates black. There are other two forms of masking that includes hard masking and soft masking. Hard masking refers to the point where the pixels affected by the masking process have their value set to the background value. The resulting intensity of the pixels, when is determined by the amount of pixels inside the region of interest is referred as soft masking. The transparency channel of an image is completely optional. While learning about image masking, you should substitute the work mask for transparency in your mind because that is what it actually means in action. Not only image masking gives you a lot of flexibility, it also gives you the option to edit your images with far better precision.