What are the different types of image restoration techniques used in computer graphics?

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What are the different types of image restoration techniques used in computer graphics?

There are several types of image restoration techniques used in computer graphics, including:

1. Spatial domain techniques: These techniques operate directly on the pixel values of the image. Examples include mean filtering, median filtering, and Wiener filtering.

2. Frequency domain techniques: These techniques involve transforming the image into the frequency domain using techniques such as Fourier Transform. Examples include high-pass filtering, low-pass filtering, and band-pass filtering.

3. Iterative techniques: These techniques involve iteratively estimating and refining the image to restore its quality. Examples include the Richardson-Lucy algorithm and the Expectation-Maximization algorithm.

4. Inpainting techniques: These techniques aim to fill in missing or damaged parts of an image. Examples include texture synthesis, exemplar-based inpainting, and patch-based inpainting.

5. Deconvolution techniques: These techniques aim to reverse the blurring effects caused by various factors such as motion blur or lens aberrations. Examples include blind deconvolution, Lucy-Richardson deconvolution, and Wiener deconvolution.

6. Super-resolution techniques: These techniques aim to enhance the resolution and details of an image. Examples include single-image super-resolution and multi-image super-resolution.

It is important to note that the choice of image restoration technique depends on the specific characteristics of the image and the type of restoration required.