Fourier Transform Coding-based Techniques for Lossless Iris Image Compression
نویسندگان
چکیده
منابع مشابه
Lossless Compression of Polar Iris Image Data
The impact of using different lossless compression algorithms when compressing biometric iris sample data from several public iris databases is investigated. In particular, the application of dedicated lossless image codecs (lossless JPEG, JPEG-LS, PNG, and GIF), lossless variants of lossy codecs (JPEG2000, JPEG XR, and SPIHT), and a few general purpose file compression schemes is compared. We ...
متن کاملTransform domain LMS-based adaptive prediction for lossless image coding
This paper is concerned with adaptive prediction for lossless image coding. A new predictor is proposed. This predictor involves two major steps: constructing a good predictor for each pixel using the transform domain LMS algorithm and adaptively combining it with a set of fixed predictors. The first step is targeting areas where simple predictors do not perform well, while the second step is a...
متن کاملLossless-by-Lossy Coding for Scalable Lossless Image Compression
This paper presents a method of scalable lossless image compression by means of lossy coding. A progressive decoding capability and a full decoding for the lossless rendition are equipped with the losslessly encoded bit stream. Embedded coding is applied to largeamplitude coefficients in a wavelet transform domain. The other wavelet coefficients are encoded by a context-based entropy coding. Th...
متن کاملThe Fourier Transform for Satellite Image Compression
The need to transmit or store satellite images is growing rapidly with the development of modern communications and new imaging systems. The goal of compression is to facilitate the storage and transmission of large images on the ground with high compression ratios and minimum distortion. In this work, we present a new coding scheme for satellite images. At first, the image will be downloaded f...
متن کاملLossless image compression using binary wavelet transform
A binary wavelet transform (BWT) has several distinct advantages over a real wavelet transform when applied to binary data. No quantisation distortion is introduced and the transform is completely invertible. Since all the operations involved are modulo-2 arithmetic, it is extremely fast. The outstanding qualities of the BWT make it suitable for binary image-processing applications. The BWT, or...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Iraqi Journal of Science
سال: 2019
ISSN: 2312-1637,0067-2904
DOI: 10.24996/ijs.2019.60.11.23