### Table 4.8: ML Mixed Gaussian Parameter Estimates and RMS Error in Amplitude Dual Tree Complex Wavelet Analysis for Log Transformed Images

in Speckle Noise Reduction via Homomorphic Elliptical Threshold Rotations in the Complex Wavelet Domain

### Table 1. A summary of the principal families of approaches and related principles, properties and functionalities.

2005

"... In PAGE 6: ... section 3). Table1 summarizes the principles, properties, and offered functionalities of the different families of approaches. ... In PAGE 7: ... Our evaluation is based on the computation times reported in the literature. Table1 shows that only the wavelet-based techniques provide both progressive transmission and scalable rendering. In particular, the irregular wavelet transform has a very low computational complexity, which makes it very attractive for mobile and real-time applications.... ..."

Cited by 1

### TABLE I. Computational complexity of wavelet transforms [3]

### Table 4.1 Multi-resolution wavelet-based image registration algorithm (one transformation only)

### Table 4.3: ML Mixed Gaussian Parameters and Estimation Error in phase for SD Complex Wavelets using Log Transformed Images

in Speckle Noise Reduction via Homomorphic Elliptical Threshold Rotations in the Complex Wavelet Domain

### Table 4.4: ML Rayleigh Estimates and RMS Error in Amplitude for SD Complex Wavelet Analysis using Log Transformed Images

in Speckle Noise Reduction via Homomorphic Elliptical Threshold Rotations in the Complex Wavelet Domain

### Table 4.7: Phase ML Mixed Gaussian Parameter Estimates and RMS Error in DT Complex Wavelet Analysis for Log Transformed Images

### Table 2: Cloud Attributes

"... In PAGE 5: ...Table 2: Cloud Attributes planes integrates the volume in smaller steps, increasing the visual opacity of the cloud. We have developed a system of equations exposing qualitatively independent parameters, summarized in Table2 . These attributes adjust the image along a single visual dimension without side-effects in an- other dimension.... ..."

### Table 1 Complexity ( G x , in operations/image) of computing wavelet histogram in WHT technique [13].

"... In PAGE 3: ... The image indexing technique based on WH is compute intensive. The complexity of WH generation is shown in Table1 . It is observed that the total complexity is approximately P B N N * ) 1 3 ( + where B N is the number of channels employed for WH generation, and P N is the total number of pixels in the image.... ..."

### Table 1: Comparison of coding results for di erent tree algorithms (wavelet tree, single tree and double tree) at various bitrates for the standard 512 512 Lena, Barbara and House images, when a single uniform quantization stepsize is used for all highpass bands. First order entropy is used as rate measure.

1996

Cited by 10