RDO ETC1 texture compression tool output

Here's what my current experimental compression tool outputs to stdout while compressing a single image. I've begun to experiment with different perceptual metrics, such as PSNR-HVS and PSNR-HVSM. (I'm somewhat leery of SSIM/MS-SSIM for this problem domain, but I still compute it.)

texexp -out kodim23.ktx -e 2048 -s 8192 -adaptive -file kodak\kodim23.png

Source filename: kodak\kodim23.png 768x512
Force ETC1S: 0 NumEndpointClusters: 2048 NumSelectorClusters: 8192 Adaptive: 1
Num failed 555 packing: 565 out of 24576 blocks, 692 out of 2048 clusters

clustered  RGB: Error: Max: 109, Mean: 2.925, MSE: 20.664, RMSE: 4.546, PSNR: 34.979, SSIM: 0.928872
clustered    R: Error: Max:  63, Mean: 3.007, MSE: 20.729, RMSE: 4.553, PSNR: 34.965, SSIM: 0.929768
clustered    G: Error: Max:  52, Mean: 2.049, MSE: 9.793, RMSE: 3.129, PSNR: 38.222, SSIM: 0.960504
clustered    B: Error: Max: 109, Mean: 3.719, MSE: 31.472, RMSE: 5.610, PSNR: 33.152, SSIM: 0.896344
clustered    Y: Error: Max:  53, Mean: 1.661, MSE: 6.830, RMSE: 2.613, PSNR: 39.787, SSIM: 0.971262

best_etc1    RGB: Error: Max:  61, Mean: 2.235, MSE: 11.225, RMSE: 3.350, PSNR: 37.629, SSIM: 0.946851
best_etc1      R: Error: Max:  50, Mean: 2.245, MSE: 10.829, RMSE: 3.291, PSNR: 37.785, SSIM: 0.952394
best_etc1      G: Error: Max:  35, Mean: 1.529, MSE: 5.260, RMSE: 2.294, PSNR: 40.921, SSIM: 0.973678
best_etc1      B: Error: Max:  61, Mean: 2.931, MSE: 17.587, RMSE: 4.194, PSNR: 35.679, SSIM: 0.914481
best_etc1      Y: Error: Max:  33, Mean: 1.231, MSE: 3.618, RMSE: 1.902, PSNR: 42.547, SSIM: 0.981130

etcpak_etc1  RGB: Error: Max: 113, Mean: 2.494, MSE: 14.325, RMSE: 3.785, PSNR: 36.570, SSIM: 0.940693
etcpak_etc1    R: Error: Max:  60, Mean: 2.637, MSE: 14.934, RMSE: 3.864, PSNR: 36.389, SSIM: 0.938706
etcpak_etc1    G: Error: Max:  65, Mean: 1.875, MSE: 8.011, RMSE: 2.830, PSNR: 39.094, SSIM: 0.964159
etcpak_etc1    B: Error: Max: 113, Mean: 2.970, MSE: 20.031, RMSE: 4.476, PSNR: 35.114, SSIM: 0.919215
etcpak_etc1    Y: Error: Max:  64, Mean: 1.497, MSE: 5.630, RMSE: 2.373, PSNR: 40.625, SSIM: 0.975777

clustered_s  RGB: Error: Max: 109, Mean: 3.065, MSE: 21.885, RMSE: 4.678, PSNR: 34.729, SSIM: 0.918469
clustered_s    R: Error: Max:  63, Mean: 3.136, MSE: 21.956, RMSE: 4.686, PSNR: 34.715, SSIM: 0.919488
clustered_s    G: Error: Max:  52, Mean: 2.241, MSE: 11.118, RMSE: 3.334, PSNR: 37.670, SSIM: 0.948531
clustered_s    B: Error: Max: 109, Mean: 3.818, MSE: 32.581, RMSE: 5.708, PSNR: 33.001, SSIM: 0.887388
clustered_s    Y: Error: Max:  53, Mean: 1.874, MSE: 8.115, RMSE: 2.849, PSNR: 39.038, SSIM: 0.959831

ETC1/2 block histogram:
ETC1_DIFFERENTIAL: 23576
ETC1_INDIVIDUAL: 1000
ETC2_T: 0
ETC2_H: 0
ETC2_PLANAR: 0

Total blocks: 24576, ETC1S: 22391 (91.109%), Diff: 23576 (95.931%), Indiv: 1000 (4.069%), Flip: 9005 (36.641%)

Wrote file kodim23.ktx

clustered_s LZMA compressed from 196676 to 89489 bytes, 1.820658 bits/texel
Best ETC1 LZMA compressed from 196676 to 130830 bytes, 2.661743 bits/texel
etcpak ETC1 LZMA compressed from 196676 to 117666 bytes, 2.393921 bits/texel

OpenCV SSIM:
R:     0.919503
G:     0.948527
B:     0.887368
Avg:   0.918466
709 L: 0.9599

basislib:
RGB Total   Error: Max: 109, Mean: 9.195, MSE: 65.655, RMSE: 8.103, PSNR: 29.958
RGB Average Error: Max: 109, Mean: 3.065, MSE: 21.885, RMSE: 4.678, PSNR: 34.729, SSIM: 0.918469
Luma        Error: Max:  53, Mean: 1.845, MSE: 7.865, RMSE: 2.805, PSNR: 39.174, SSIM: 0.959831
Red         Error: Max:  63, Mean: 3.136, MSE: 21.956, RMSE: 4.686, PSNR: 34.715, SSIM: 0.919488
Green       Error: Max:  52, Mean: 2.241, MSE: 11.118, RMSE: 3.334, PSNR: 37.670, SSIM: 0.948531
Blue        Error: Max: 109, Mean: 3.818, MSE: 32.581, RMSE: 5.708, PSNR: 33.001, SSIM: 0.887388

PSNR-HVS:  85.836
PSNR-HVSM: 90.828

Experiment succeeded.

The tool outputs over a dozen debug images. Here's some of the compressor prototype's output: