Abstract: In this paper, the various research papers related to ‘embedded image compression’ are studied. The aim of the present work is to study the methods adopted and analysis and results obtained. The different methods are adopted by various researchers. The present paper includes discrete wavelet transform (DWT), such as embedded zero wavelet (EZW) and the set partitioning in hierarchical trees (SPIHT) are studied. Block based discrete cosine transform (DCT) encoders are used in many image and video coding standards. Wavelet-based image coders such as embedded zero tree wavelet (EZW) coder, set partitioning in hierarchical trees (SPIHTs), set partitioning embedded block (SPECK), morphological representations of wavelet data (MRWD) and significance-linked connected component analysis (SLCC) are also the part of embedded image compression. Different types of redundancy present in an image, such as Spatial Redundancy, Statistical Redundancy and Human Vision Redundancy are very necessary for analysis. The JPE -2OOU image compression standard is increasingly gaining widespread importance. Ultra spectral imaging is a relatively recent development which makes quantitative remote sensing of the Earth’s surface possible.Abstract: In this paper, the various research papers related to ‘embedded image compression’ are studied. The aim of the present work is to study the methods adopted and analysis and results obtained. The different methods are adopted by various researchers. The present paper includes discrete wavelet transform (DWT), such as embedded zero wavelet (EZW) and ...Show More
Abstract: The main objective of this study is to show the importance of the Difference in Difference (DiD) method and its applicability in the field of human and social sciences. The DiD method is one of the famous tools in econometrics to investigate the causal effect of the policy before and after treatment or policy. Why difference in difference method is most important in these days? Because the traditional methods requires more instructions as compare to DiD method which is easier and applicable without randomization of the data. The difference is compared with treated and non-treated group in two time’s period model with the same unit of data. The first difference removes the time-invariant factors while Difference in Difference removes the time-variant factors of the model and the remaining statistic shows the original impact of the treatment or policy.Abstract: The main objective of this study is to show the importance of the Difference in Difference (DiD) method and its applicability in the field of human and social sciences. The DiD method is one of the famous tools in econometrics to investigate the causal effect of the policy before and after treatment or policy. Why difference in difference method is...Show More
