Search results for "Image compression"
showing 3 items of 53 documents
Space-Frequency Quantization for Image Compression With Directionlets
2007
The standard separable 2-D wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to efficiently capture 1-D discontinuities, like edges or contours. These features, being elongated and characterized by geometrical regularity along different directions, intersect and generate many large magnitude wavelet coefficients. Since contours are very important elements in the visual perception of images, to provide a good visual quality of compressed images, it is fundamental to preserve good reconstruction of these directional features. In our previous work, we proposed a construction of critic…
American College of Cardiology/ European Society of Cardiology international study of angiographic data compression phase III. Measurement of image q…
2000
Objectives We sought to investigate up to which level of Joint Photographic Experts Group (JPEG) data compression the perceived image quality and the detection of diagnostic features remain equivalent to the quality and detectability found in uncompressed coronary angiograms. Background Digital coronary angiograms represent an enormous amount of data and therefore require costly computerized communication and archiving systems. Earlier studies on the viability of medical image compression were not fully conclusive. Methods Twenty-one raters evaluated sets of 91 cine runs. Uncompressed and compressed versions of the images were presented side by side on one monitor, and image quality differe…
Image classification based on 2D feature motifs
2013
The classification of raw data often involves the problem of selecting the appropriate set of features to represent the input data. In general, various features can be extracted from the input dataset, but only some of them are actually relevant for the classification process. Since relevant features are often unknown in real-world problems, many candidate features are usually introduced. This degrades both the speed and the predictive accuracy of the classifier due to the presence of redundancy in the candidate feature set. In this paper, we study the capability of a special class of motifs previously introduced in the literature, i.e. 2D irredundant motifs, when they are exploited as feat…