This document discusses lossy light field compression techniques. It introduces the plenoptic function and different light field representations like texture, depth maps, and point clouds. It then examines existing 2D and 3D image compression standards that can be applied to light fields, such as JPEG, H.264, and JPEG 2000. The document presents results comparing the performance of 2D JPEG 2000 and 3D JPEG 2000 compression on sample 8x8 camera array and Lytro Illum light field data, showing that 3D JPEG 2000 provides better compression at equivalent quality levels.

1. Lossy Light Field Compression
David Barina
November 13, 2018

2. Plenoptic function
P(x, y, z, θ, φ, λ, t)

3. Plenoptic function: representations
texture, depth map, point cloud, light field, hologram

4. 4D Light Field (Lytro Illum)

5. 4D Light Field (8 × 8 camera array)

6. 4D Light Field (8 × 8 camera array)

7. Light field compression
existing work
2D images (independent): JPEG, JPEG 2000, JPEG XR,
SPIHT, H.264, H.265
2D images (video coding): H.264, H.265
3D volume: 3D DCT (weird)
not seen
2D images (independent): AVIF
2D images (video coding): AV1
3D volume: JP3D (JPEG 2000: Part 10), 3D JPEG
4D hypervolume: 4D JPEG, 4D JPEG 2000

8. Results (8 × 8 camera array)
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55
0 2 4 6 8 10 12 14 16
PSNR[dB]
bitrate [bpp]
2D JPEG 2000
3D JPEG 2000

9. Results (Lytro Illum)
15
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25
30
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40
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50
55
0 2 4 6 8 10 12 14
PSNR[dB]
bitrate [bpp]
2D JPEG 2000
3D JPEG 2000