Why is Image<TPixel> a generic class?
We support multiple pixel formats just like System.Drawing does. However, unlike their closed PixelFormat enumeration, our solution is extensible.
A pixel is basically a small value object (struct), describing the color at a given point according to a pixel model we call Pixel Format.
Image<TPixel> represents a pixel graphic bitmap stored as a generic, discontiguous memory block of pixels, of total size
image.Width * image.Height. Note that while the image memory should be considered discontiguous by default, if the image is small enough (less than ~4GB in memory, on 64-bit), it will be stored in a single, continuous memory block for improved performance. The reason why there is additional support for discontiguous buffers is to allow images at super high resolution, which couldn't otherwise be loaded due to limitations to the maximum size of objects in the .NET runtime, even on 64-bit systems.
In the case of multi-frame images multiple bitmaps are stored in
Choosing Pixel Formats
Take a look at the various pixel formats available under SixLabors.ImageSharp.PixelFormats After picking the pixel format of your choice, use it as a generic argument for Image<TPixel>, for example, by instantiating
Defining Custom Pixel Formats
Creating your own pixel format is a case of defining a struct implementing IPixel<TSelf> and using it as a generic argument for Image<TPixel>. Baseline batched pixel-conversion primitives are provided via PixelOperations<TPixel> but it is possible to override those baseline versions with your own optimized implementation.
Is it possible to store a pixel on a single bit for monochrome images?
No. Our architecture does not allow sub-byte pixel formats at the moment. This feature is incredibly complex to implement, and you are going to pay the price of the low memory footprint in processing speed / CPU load.
Unfortunately it's not possible and is unlikely to be in the future. Many image processing operations expect the pixels to be laid out in-memory in RGBA format. To manipulate images in exotic colorspaces we would have to translate each pixel to-and-from the colorspace multiple times, which would result in unusable performance and a loss of color information.