Compressive-Projection Principal Component Analysis

  title={Compressive-Projection Principal Component Analysis},
  author={James E. Fowler},
  journal={IEEE Transactions on Image Processing},
Principal component analysis (PCA) is often central to dimensionality reduction and compression in many applications, yet its data-dependent nature as a transform computed via expensive eigendecomposition often hinders its use in severely resource-constrained settings such as satellite-borne sensors. A process is presented that effectively shifts the computational burden of PCA from the resource-constrained encoder to a presumably more capable base-station decoder. The proposed approach… CONTINUE READING
Highly Influential
This paper has highly influenced 16 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 130 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 75 extracted citations

130 Citations

Citations per Year
Semantic Scholar estimates that this publication has 130 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.

Similar Papers

Loading similar papers…