A gray image compression using a Hilbert scan

Preprocessing Methods for Improved Lossless Compression of Color Look-up Tables

“…A serialization of the data in this order results in a discontinuous step in the 2D CLUT coordinates due to the jump from the end of a line to the start of the next. To eliminate these discontinuities that are artificially induced by the data serialization, we propose instead to obtain the one-dimensional data through the traversal of the multidimensional CLUT along a space filling curve [11][12][13][14] that assures that the data are traversed in a manner that preserves continuity in the input space of the multidimensional CLUT. Specifically, in this work we use the C-scan ordering shown in Fig.…”

Efficient algorithms for coding Hilbert curve of arbitrary-sized image and application to window query

“…Previously, Liu and Schrack [27,28] presented efficient encoding and decoding algorithms to map 2-D/3-D images to Hilbert curves. Based on the Hilbert curve representation, many applications [3,4,6,8,10,18,[23][24][25]35,36,39,43,11,9,15,5,29] have been developed. These Hilbert curvebased applications all suffer from the common constraint that the given image must be of size 2 r · 2 r .…”

Quad-splitting algorithm for a window query on a Hilbert curve

“…If the original image is represented by a set of codes, it achieves the compression effect. Based on the Hilbert scan and the zero-order interpolation, Kamata et al proposed two algorithms for compressing gray images [18] and color images [19], respectively. Jian proposed an algorithm [8] for compressing a gray image by using the first-order interpolation and the split point approximation.…”

“…Kamata et al proposed a computation method using lookup table [17] and applied it to compress an image [18,19]. Chung et al applied Liu and Schrack's encoding formula [22] to obtain the corresponding Hilbert orders and compress an image [8].…”

“…Moreover, the scanning order of Hilbert curve is named as Hilbert scan. Recently, some image compression methods based on Hilbert scan have been proposed [8,9,17,18,19]. Those methods are based on the Hilbert neighborhood property by a segmentation of the scanned one-dimensional data using the linear interpolation.…”