Is There a Sparse Representation for Noise?

1. What is meant by sparse representation?
2. What is sparse representation of an image?
3. What is sparse representation classification?
4. What is sparse representation in machine learning?

What is meant by sparse representation?

Sparse representations intend to represent signals with as few as possible significant coefficients. This is important for many applications, like for instance compression. When using wavelets it is frequently noticed that a great compression rate can be obtained, with almost unnoticeable loss of information.

What is sparse representation of an image?

In the image sparse representation model, it is assumed that there exists an over-complete dictionary, and the image can be represented as a linear combination of dictionary atoms.

What is sparse representation classification?

Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels.

What is sparse representation in machine learning?

Sparse representation is a parsimonious principle that a signal can be approximated by a sparse superposition of basis functions. The main topic of my thesis research is to apply this principle in the machine learning fields including classification, feature extraction, feature selection, and optimization.