Image Compression using Principal Component Analysis
Hadjer Moulay Omar, Marwa Morsli, Salah Yaichi
Abstract
The image has touched several areas of our lives, so we need to have well-shaped images with less and less sizes. In this paper, we present an image compression technique based on Principal Component Analysis (PCA). It is based on the reduction of the image vectors of the image using the principal ones with multiple factors. The obtained results using PCA clearly show that this technique gives good results with uncorrelated and redundant data. The compression ratio was entirely affected by the number of bits reserved to represent the real factors associated to PCA vectors.
Topics & Concepts
Principal component analysisImage compressionPattern recognition (psychology)Artificial intelligenceData compressionCompression (physics)Image (mathematics)Computer scienceUncorrelatedComputer visionMathematicsImage processingStatisticsComposite materialMaterials scienceSpectroscopy and Chemometric AnalysesBlind Source Separation TechniquesImage and Signal Denoising Methods