際際滷shows by User: jumleshashaik / http://www.slideshare.net/images/logo.gif 際際滷shows by User: jumleshashaik / Wed, 20 Aug 2014 23:42:07 GMT 際際滷Share feed for 際際滷shows by User: jumleshashaik Ml srhwt-machine-learning-based-superlative-rapid-haar-wavelet-transformation-for-digital-image-coding /slideshow/ml-srhwtmachinelearningbasedsuperlativerapidhaarwavelettransformationfordigitalimagecoding/38199911 ml-srhwt-machine-learning-based-superlative-rapid-haar-wavelet-transformation-for-digital-image-codi-140820234208-phpapp01
Abstract: In this paper a digital image coding technique called ML-SRHWT (Machine Learning based image coding by Superlative Rapid HAAR Wavelet Transform) has been introduced. Compression of digital image is done using the model Superlative Rapid HAAR Wavelet Transform (SRHWT). The Least Square Support vector Machine regression predicts hyper coefficients obtained by using QPSO model. The mathematical models are discussed in brief in this paper are SRHWT, which results in good performance and reduces the complexity compared to FHAAR and EQPSO by replacing the least good particle with the new best obtained particle in QPSO. On comparing the ML-SRHWT with JPEG and JPEG2000 standards, the former is considered to be the better.]]>
Abstract: In this paper a digital image coding technique called ML-SRHWT (Machine Learning based image coding by Superlative Rapid HAAR Wavelet Transform) has been introduced. Compression of digital image is done using the model Superlative Rapid HAAR Wavelet Transform (SRHWT). The Least Square Support vector Machine regression predicts hyper coefficients obtained by using QPSO model. The mathematical models are discussed in brief in this paper are SRHWT, which results in good performance and reduces the complexity compared to FHAAR and EQPSO by replacing the least good particle with the new best obtained particle in QPSO. On comparing the ML-SRHWT with JPEG and JPEG2000 standards, the former is considered to be the better.]]> Wed, 20 Aug 2014 23:42:07 GMT /slideshow/ml-srhwtmachinelearningbasedsuperlativerapidhaarwavelettransformationfordigitalimagecoding/38199911 jumleshashaik@slideshare.net(jumleshashaik) Ml srhwt-machine-learning-based-superlative-rapid-haar-wavelet-transformation-for-digital-image-coding jumleshashaik Abstract: In this paper a digital image coding technique called ML-SRHWT (Machine Learning based image coding by Superlative Rapid HAAR Wavelet Transform) has been introduced. Compression of digital image is done using the model Superlative Rapid HAAR Wavelet Transform (SRHWT). The Least Square Support vector Machine regression predicts hyper coefficients obtained by using QPSO model. The mathematical models are discussed in brief in this paper are SRHWT, which results in good performance and reduces the complexity compared to FHAAR and EQPSO by replacing the least good particle with the new best obtained particle in QPSO. On comparing the ML-SRHWT with JPEG and JPEG2000 standards, the former is considered to be the better. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ml-srhwt-machine-learning-based-superlative-rapid-haar-wavelet-transformation-for-digital-image-codi-140820234208-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Abstract: In this paper a digital image coding technique called ML-SRHWT (Machine Learning based image coding by Superlative Rapid HAAR Wavelet Transform) has been introduced. Compression of digital image is done using the model Superlative Rapid HAAR Wavelet Transform (SRHWT). The Least Square Support vector Machine regression predicts hyper coefficients obtained by using QPSO model. The mathematical models are discussed in brief in this paper are SRHWT, which results in good performance and reduces the complexity compared to FHAAR and EQPSO by replacing the least good particle with the new best obtained particle in QPSO. On comparing the ML-SRHWT with JPEG and JPEG2000 standards, the former is considered to be the better.
Ml srhwt-machine-learning-based-superlative-rapid-haar-wavelet-transformation-for-digital-image-coding from Jumlesha Shaik
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