### Table 11: The impact of separability to the VaR in case of bilinear interpolation

### Table 11: The impact of separability to the VaR in case of bilinear interpolation

1997

### Table 3 Differences of estimated heights (cleaned data) to heights bilinearly interpolated in the reference DTM

"... In PAGE 7: ... 7 Table3 represents the accuracy of our matching approach. The accuracy is in the subpixel level! The figures of Table 5 are worse due to interpolation errors (330,000 points were interpolated from 16,000 - 20,000 points).... In PAGE 7: ... The results for map sheet 1225 are worse due to the mountainous terrain, many forests and the lake. With denser measurement points they should be close to the results of map sheet 1224 as Table3 also indicates. Version 1 (without constraints) is surprisingly good.... In PAGE 7: ... The improvement of the results due to blunder detection is remarkable. Table3 shows the same results as Table 3 but for the raw data (including blunders). The results are as the average 37% worse than those of Table 3.... ..."

### Table 4.4. Mean error angles of tree sequences using staircase and bilinear interpolation.

### Table 1 Differences of estimated heights (cleaned data) to heights bilinearly interpolated in the reference DTM (in me- ters)

"... In PAGE 6: ... The case of affine transformation was excluded a priori because in many cases it is not stable since the selected points lie at edges and thus two scales and one shear are often not determinable. Table1 shows the difference between the 34000 - 38000 matched points and the reference DTM, whereby the cleaned data refer to the matching results after automatic blunder detection. In the here presented test, the same points were matched but their approximations were derived by a hierarchical approach using image pyramids.... ..."

### Table 1: Interpolation Filters: Optimal and Bilinear

"... In PAGE 4: ...Table 1: Interpolation Filters: Optimal and Bilinear and the aliasing error AE = jjH(?z)G(z)X(?z)jj2; introduced by the sampling process, where X(z) is the Z-transform of a step signal. Optimal interpolation lters G(z) can be found in this way for di erent lter lengths n, and they are given in Table1 (a) for DF=2, along with two PSNR values: PSNR1 corresponds to the PSNR obtained with a step signal, while PSNR2 corresponds to the PSNR obtained when applying steps 1 and 4 in the horizontal direction to a real image (Figure 4). Note that little PSNR improvement results from examining lters longer than n = 6.... In PAGE 4: ... Note that little PSNR improvement results from examining lters longer than n = 6. Table1 (a) also contains the PSNR performance of the bilinear interpolation lter. Its PSNR performance is about 1 dB below that of the best optimal lters.... In PAGE 5: ...the one corresponding to a PSNR improvement over no pixel averaging. As a consequence, for all values of the DF used in the following experiments, we will consider only bilinear interpolation lters, coe cients of which are given in Table1 (b). 2 3 4 5 6 7 15 20 25 30 35 Log2(Compression Ratio) Peak-Signal-to-Noise Ratio (PSNR in dB) * : H1V1 + : H2V1 + BILIN --: H2V1 + (n=6) Figure 2: MSE (PSNR) Performance Comparison between Bilinear and Optimal Interpola- tion Filters combined with Lossy JPEG 3 Image Description and Compression Assessment The lander is in the shape of a tetrahedron.... ..."

### Table 1: Average PSNR (dB) improvement over bilinear interpolation for the 25 images for each color channel and the whole image

"... In PAGE 4: ....4. Experimental results To verify the effectiveness of our approach, we applied the filters corresponding to Vdd1 and Vdd2 on a set of 25 Kodak images and compared the results with the nominal Vdd case and the signal correlation method [6]. Table1 presents the average PSNR for R, G, B color channels and the whole image. At nominal Vdd, our method produces better results than signal correlation.... ..."

### Table 1: Average PSNR (dB) improvement over bilinear interpolation for the 25 images for each color channel and the whole image

"... In PAGE 4: ....4. Experimental results To verify the effectiveness of our approach, we applied the filters corresponding to Vdd1 and Vdd2 on a set of 25 Kodak images and compared the results with the nominal Vdd case and the signal correlation method [6]. Table1 presents the average PSNR for R, G, B color channels and the whole image. At nominal Vdd, our method produces better results than signal correlation.... ..."

### TABLE I AVERAGE PSNR [DB] FOR: BILINEAR INTERPOLATION (BI), THE ADAPTIVE MAP APPROACH [4] AND THE PROPOSED METHOD, FOR p LOST PACKETS

### Table 1 The absolute differences between the bilinear and the cubic spline interpolation algorithms, along with and accumulations. The image (2563256) was enlarged

"... In PAGE 7: ... It is noted that the histogram is computed after applying a round-up operation ages produced by the bilinear interpolation spline interpolation algorithms. Table1 shows ences between the bilinear interpolation Fig. 15 Pixel maps where the cubic spline interpolation is used (prediction test 2 with T521): (a) horizontally reduced by 1/ amp;, (b) vertically reduced by 1/ amp;, (c) horizontally enlarged by amp;, and (d) vertically enlarged by amp;.... ..."