### Table 2: Performance of quadtree type fractal image compression with and without isometries.

1996

Cited by 8

### Table 1: Satellite image compression with individual bands fractal-coded

### Table 4: Fractal computation comparision on SUN SPARCstation 2 and RS6000 platforms using PVM

"... In PAGE 5: ... From the communication performance study a very low e ciency of the RS6000 system is evident . How it in uences the speedup and e ciency of the fractal computation is shown in Table4 for the PVM platform. There are some possibilities to im- prove a processor farm computation when the model B of farm instead A is used for a greater number of processors.... In PAGE 7: ... For the ray tracing computations ve RS-6000 are doing better than seven SPARCstation2. This result is opposite to that reported in Table4 . In general, it was possible to speedup the ray tracing computation by 51 times via distributed computing in the heterogeneous environ- ment built of the seven SPARCstation2, ve RS-6000 and one HP9000/720 .... ..."

Cited by 1

### Table 8: PVM Compositing Communication Times on the Vorticity Data Set

"... In PAGE 30: ... Table8 : PVM Compositing Communication Times with Compression on the Vorticity Data Set... ..."

### Table 1. Results of fractal image compression using self-organizing domain classification (method SO ), domain comparison using features only ( FO ), and the baseline fractal image compression method ( Base ).

"... In PAGE 3: ... 5. Results Table1 compares fractal image compression results using three different methods applied to the images shown in Figures 1 and 2. The baseline ( Base ) method is the standard quadtree method as discussed in [2], with no domain classification.... ..."

### Table 1. Results of fractal image compression using self-organizing domain classification (method SO ), domain comparison using features only ( FO ), and the baseline fractal image compression method ( Base ).

"... In PAGE 3: ... 5. Results Table1 compares fractal image compression results using three different methods applied to the images shown in Figures 1 and 2. The baseline ( Base ) method is the standard quadtree method as discussed in [2], with no domain classification.... ..."

### Table 1: Performance of fractal image compression with and without isometries. The partitioning of the images are of xed range block size.

1996

"... In PAGE 2: ...ere computed using full search, i.e., all domains (with all of their isometric versions, if needed) are checked. The results for the well known test images Lenna, Peppers, and Mandrill are given in Table1 . The im- ages are encoded 18 times with di ering parameters: the domain pool size is large, medium, or small; the partitioning is made from blocks of size 4 4, 8 8, or 16 16, and the encodings use the codebook generated from the domain pool with isometries or a codebook of the same size obtained from a plain domain pool.... ..."

Cited by 8

### Table 3: Performance of fractal image compression with (columns `+=? apos;) and without (columns `+ apos;) scaling factors.

1996

"... In PAGE 3: ... Thus, for such cases we are fair and compare en- codings with the same time complexity. Table3 gives the results for xed block size parti- tionings and in Table 4 variable rate encodings with quadtrees are considered as in the last section. Here the situation is not as clear as with isometries, at least not for small ranges of size 4 by 4 pixels, where a qual- ity deterioration of up to 1 dB is observed.... ..."

Cited by 8

### Table 3. De-Noising performance for the fractal-compressed \Lenna quot; images

1995

Cited by 4