Joint Video Experts Team (jvet) of itu-t sg 6 wp and iso/iec jtc 1/sc 29/wg 11

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6.7CE7: Quantization and coefficient coding (12)

JVET-K0027 CE7 summary report on quantization and coefficient coding [H. . Schwarz, M. . Coban]

The CE report summarizes the test results and cross check reports for the CE7 on quantization and coefficient coding. The following subtests are included in the CE:

Subtest 7.1: Comparison of 4 proposals for entropy coding of transform coefficient levels

This subtest was discussed 0900 Friday 13 July (chaired by GJS).

Overall gain relative to the VTM for these proposals was about 1.5/0.9/0.6 for AI/RA/LB. All proposals seemed roughly in that ballpark. All of them used about the same number of contexts (123–156).

The Samsung proposal 7.1.3 had a difference of initialization method, using 0.5 probability initialization. Variation (1) in the summary table tries to compensate for this by changing the reference to also use that initialization. The difference between the two was 0.0/0.2/0.6 for AI/RA/LB in the VTM.

There was also a difference in the VTM testing in the coding of remaining coefficients, where the Samsung proposal did not use additional features found in the BMS but others did. The proponent suggested focusing on the BMS results to avoid that difference of ~0.25%.

A proponent remarked that the method of training the context initialization was not known in general in this test for most technologies tested.

Test 7.1.2 is a scheme compatible with the K0071 trellis quantization method, but with that aspect disabled. A participant remarked that this scheme might have throughput issues due to the way that scheme could have a high number of context coded bins in the worst case.
Subtest 7.2: Comparison of dependent quantization and sign data hiding

This subtest was discussed 1920-2000 Thursday 12 July (chaired by GJS).

K0072 This has two sets of quantization reconstruction levels and a state machine to choose between them. The parity of the coefficient is used in the state machine. From the encoder perspective, it is suggested to be basically trellis coded quantization.

This uses double the number of context models for the significance flag and the absolute level greater than 1 flag.

The gain over the VTM is 5.0%/3.4%/2.7% for AI/RA/LD. The gain over the BMS is 2.5%/1.9%/1.6%. The encoder impact is about 10-13%.

This effectively has a combination of quantization and entropy coding together.

It was commented that were several relevant non-CE contributions which should be taken into account.

It was commented that also we need a fall-back mode that does not require encoder trellis search.

The decoding process is a bit more complicated.

This should be considered for testing with non-CE contributions in a CE. It was commented that at least one of the non-CE approaches is better and may be considered instead.

Subtest 7.3: Investigation of 3 approaches related the derivation and signalling of quantization step sizes

This subtest was discussed 0945 Friday 13 July (chaired by GJS).

There were three proposals in this area.

  • K0140 (with two variants) has a scaling based on neighbouring samples. This is perceptually motivated, and detrimental to PSNR, but shows some gain in MSSIM.

    • Variant 1 uses reconstructed neighbours to control inverse quantization. It appeared that this has an unacceptable impact on decoding complexity.

    • Variant 2 scales the spatial-domain residual signal using reconstructed samples.

    • It was commented that encoder-side tricks can alternatively be used – e.g., using MS-SSIM for mode decisions or using adaptive delta-QP control.

    • This “bakes in” a specific criterion for the QP control.

    • Encoder tricks can also be combined with this. The proponent said that a combination of this scheme and encoder perceptual R-D control could provide roughly a MOS difference of 0.3.

    • There might be a different desired behaviour for PQ vs. HLG vs. SDR, 4:2:0 vs. 4:4:4, YCbCr vs. RGB, and other application-specific circumstances.

    • Very similar concepts have arisen in the HDR studies.

    • Hypothetically, we could end up with several different selectable automatic QP adjustment schemes, if we want to build in such automatic schemes.

    • This does QP control at a finer granularity than what an encoder would typically use, which may or may not be desirable.

    • It was commented that restricting such a scheme to only larger block regions may be desirable.

    • This adds some processing (a scaling of the residual signal) and has a serialization dependency (using neighbour samples to control current block processing).

    • As tested, the deblocking is not accounting for the scaling change.

    • Further study was encouraged, with consideration of the above-identified issues.

  • K0251 proposed increasing the upper bound on QP by 6 (no effect on CTC)

    • The upper limit actually was encountered in CfP high QP use for RA conditions

    • Several participants commented that this had been encountered in a product, where quantization matrices need to be used to get around the issue.

    • For deblocking, an extrapolation of the current behaviour is used (specifics are in software)

    • The chroma QP derivation change is straightforward

    • Decision: Adopt – extending the range by 12 (pending spec text)

    • It was commented that in the future we should also think about the granularity of step sizes.

  • K0252 proposed a different way of deriving chroma QP from luma QP

    • This proposes a change of the mapping function for deriving chroma QP by establishing a maximum difference between the input and output QPs of the matching function.

    • The cross-checker commented that there were other ways to adjust chroma QP

    • It ws noted that RExt has an ability to change the chroma QP on a block basis

    • A participant remarked that the chroma QP derivation function can cause strange effects in rate control since the R-D behaviour of the chroma is different from that for the luma

    • It was commented that QP also affects deblocking and that relationship should be studied.

    • Further study was encouraged, with a desire to establish a less ad-hoc manner of dealing with chroma QP.

Subtest 7.4: Investigation of an approach for modifying the scanning order of transform coefficients

This subtest was discussed 1042 Friday 13 July (chaired by GJS).

This proposal modifies the scanning order of transform coefficients based on block shapes. The reported gain was 0.3%/0.1%/0.1% for AI/RA/LB relative to the VTM and basically no gain over BMS.

HEVC has a dependency on the intra prediction mode for the scan order. That was removed when designing the first draft of VVC.

It was commented that this has some interaction with NSST and other aspects of coefficient coding.

This should be further studied together with secondary transforms and other aspects of coefficient coding

Subtest 7.5: Comparison of two configurations for transform domain sign prediction

This subtest was discussed 1050 Friday 13 July (chaired by GJS).

Test 7.5.1 (K0044) performs residual sign prediction in the transform domain, predicting up to 5 signs per transform block. The inverse transform requires the reconstructed samples of the neighbour blocks. This has a serious complexity impact (as per above with K0140). This also has a very significant impact on decoder runtime. The gain over the VTM is reported as 1.3%/1.0%/0.7% for AI/RA/LB.

Test 7.5.2 is the same, but only used for intra.

Further study was recommended. A way to avoid the serial dependency is especially needed.
JVET-K0044 CE7: Residual sign prediction in transform domain (Tests 7.5.1 and 7.5.2) [A. . Filippov, A. . Karabutov, V. . Rufitskiy, J. . Chen (Huawei)]
JVET-K0069 CE7: Coefficient Coding (Test 1.1) [M. . Coban, J. . Dong, T. . Hsieh, M. . Karczewicz (Qualcomm)]
JVET-K0071 CE7: Transform coefficient coding and dependent quantization (Tests 7.1.2, 7.2.1) [H. . Schwarz, T. . Nguyen, D. . Marpe, T. . Wiegand (Fraunhofer HHI)]
JVET-K0138 CE7.1.3: Scan Region-based Coefficient Coding [Y. . Piao, W. . Choi, C. . Kim (Samsung)]
JVET-K0140 CE7: Adaptive quantization step size scaling (Test 7.3.1) [Y. . Zhao, H. . Yang, J. . Chen (Huawei)]
JVET-K0251 CE7.3.2: Extension of quantization parameter value range [S.-T. Hsiang, S.-M. Lei (MediaTek)]
JVET-K0252 CE7.3.3: Derivation of chroma QP from luma QP [S.-T. Hsiang, S.-M. Lei (MediaTek)]
JVET-K0321 CE 7.1.4: JEM 7.0 coefficient coding with complexity reduction [C. . Auyeung, J. . Chen (Huawei)]
JVET-K0398 CE7: Block size dependent coefficient scanning (CE7.4.1) [Y. . Kidani, K. . Kawamura, S. . Naito (KDDI)] [late]
JVET-K0457 Crosscheck for CE7-1.2 [M. . Gao, W. . Zhang (Hulu)] [late]
JVET-K0459 Crosscheck for CE7-5.1 [M. . Gao, W. . Zhang (Hulu)] [late]

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