A Study Of The Discrete Hartley Transform For Image Compression Applications

<title>Recent studies of transform image enhancement</title>

“…We tried the radial Gaussian and Butterworth type filters whose transfer functions are given by F1(f) = exp[_I (5) for Gaussian type, and F2(f) = 1f2 (6) for the Butterworth type, where f is equal to \/fTT is the radial frequency. In Eq.…”

Transform image enhancement

“…The discrete cosine-III transform (DC3T) has computational complexity midway between the SRDFT and DCT, and has the best performance in terms of the mean-square reconstruction error and visual criteria.8 Another application of real transforms for coding is discussed in Ref. 9. An additional advantage of transform image enhancement techniques is low complexity of computations if they are implemented together with transform image coding.…”

Fast computation of the discrete Hartley transform

“…Over the years, the discrete Hartley transform (DHT) [1] has been established as a potential tool for signal processing and communication applications, e.g. computation of convolution and deconvolution [2][3][4][5], interpolation of real-valued signal [6], image compression [7][8][9][10][11], error control coding [12], adaptive filtering [13][14][15][16], multi-carrier modulation and many other applications [17][18][19][20]. The DHT is known due to its real-valued symmetric transform kernel, which is identical to that of its inverse.…”

“…, the DCTs: G 1 [k] and G 2 [k], respectively, can be realized with an IIR filter structure, as shown inFigure 2. We then obtain H 2 [k] = G 1 [k]+G 2 [k] (due to(7)). H 1 [k] is obtained as N /2 point DHT of x[2n] samples.…”