DCT stands for Discrete Cosine Transform. It is a member of the family of Fourier transforms. Hence it computes/displays the amount and distribution of spectral components of the signal being transformed. Its distinguishing feature isfeatures are that it produces real transform coefficients, it is computed using only real arithmetic and it packs signal energy into low frequency components (thats why it is used in transform based data compression algorithms). For data compression purposes DCT is only an example of other available methods and it serves only the beginnig part of such codecs. You must also consider code designentropy based coding, perceptual metric evaluation and Quantizer design issues to realize any practical benefits from such transforms.
DCT stands for Discrete Cosine Transform. It is a member of the family of Fourier transforms. Hence it computes/displays the amount and distribution of spectral components of the signal being transformed. Its distinguishing feature is that it produces real transform coefficients, it is computed using only real arithmetic and it packs signal energy into low frequency components (thats why it is used in transform based data compression algorithms). For data compression purposes DCT is only an example of other available methods and it serves only the beginnig part of such codecs. You must also consider code design and Quantizer design issues to realize any practical benefits from such transforms.
DCT stands for Discrete Cosine Transform. It is a member of the family of Fourier transforms. Hence it computes/displays the amount and distribution of spectral components of the signal being transformed. Its distinguishing features are that it produces real transform coefficients, it is computed using only real arithmetic and it packs signal energy into low frequency components (thats why it is used in transform based data compression algorithms). For data compression purposes DCT is only an example of other available methods and it serves only the beginnig part of such codecs. You must also consider entropy based coding, perceptual metric evaluation and Quantizer design issues to realize any practical benefits from such transforms.
DCT stands for Discrete Cosine Transform. It is a member of the family of Fourier transforms. Hence it computes/displays the amount and distribution of spectral components of the signal being transformed. Its distinguishing feature is that it produces real transform coefficients, it is computed using only real arithmetic and it packs signal energy into low frequency components (thats why it is used in transform based data compression algorithms). For data compression purposes DCT is only an example of other available methods and it serves only the beginnig part of such codecs. You must also consider code design and Quantizer design issues to realize any practical benefits from such transforms.