Lee Prangnell

Lee Prangnell, Victor Sanchez

There exists an intrinsic relationship between the spectral sensitivity of the Human Visual System (HVS) and colour perception; these intertwined phenomena are often overlooked in perceptual compression research. In general, most previously proposed visually lossless compression techniques exploit luminance (luma) masking including luma spatiotemporal masking, luma contrast masking and luma texture/edge masking. The perceptual relevance of color in a picture is often overlooked, which constitutes a gap in the literature. With regard to the spectral sensitivity phenomenon of the HVS, the color channels of raw RGB 4:4:4 data contain significant color-based psychovisual redundancies. These perceptual redundancies can be quantized via color channel-level perceptual quantization. In this paper, we propose a novel spatiotemporal visually lossless coding method named Spectral Perceptual Quantization (Spectral-PQ). With application for RGB 4:4:4 video data, Spectral-PQ exploits HVS spectral sensitivity-related color masking in addition to spatial masking and temporal masking; the proposed method operates at the Coding Block (CB) level and the Prediction Unit (PU) level in the HEVC standard. Spectral-PQ perceptually adjusts the Quantization Step Size (QStep) at the CB level if high variance spatial data in G, B and R CBs is detected and also if high motion vector magnitudes in PUs are detected. Compared with anchor 1 (HEVC HM 16.17 RExt), Spectral-PQ considerably reduces bitrates with a maximum reduction of approximately 81%. The Mean Opinion Score (MOS) in the subjective evaluations show that Spectral-PQ successfully achieves perceptually lossless quality.

Lee Prangnell, Victor Sanchez

In perceptual image coding applications, the main objective is to decrease, as much as possible, Bits Per Pixel (BPP) while avoiding noticeable distortions in the reconstructed image. In this paper, we propose a novel perceptual image coding technique, named Perceptual Color Compression (PCC). PCC is based on a novel model related to Human Visual System (HVS) spectral sensitivity and CIELAB Just Noticeable Color Difference (JNCD). We utilize this modeling to capitalize on the inability of the HVS to perceptually differentiate photons in very similar wavelength bands (e.g., distinguishing very similar shades of a particular color or different colors that look similar). The proposed PCC technique can be used with RGB (4:4:4) image data of various bit depths and spatial resolutions. In the evaluations, we compare the proposed PCC technique with a set of reference methods including Versatile Video Coding (VVC) and High Efficiency Video Coding (HEVC) in addition to two other recently proposed algorithms. Our PCC method attains considerable BPP reductions compared with all four reference techniques including, on average, 52.6% BPP reductions compared with VVC (VVC in All Intra still image coding mode). Regarding image perceptual reconstruction quality, PCC achieves a score of SSIM = 0.99 in all tests in addition to a score of MS-SSIM = 0.99 in all but one test. Moreover, MOS = 5 is attained in 75% of subjective evaluation assessments conducted.

Lee Prangnell, Victor Sanchez

Due to the spectral sensitivity phenomenon of the Human Visual System (HVS), the color channels of raw RGB 4:4:4 sequences contain significant psychovisual redundancies; these redundancies can be perceptually quantized. The default quantization systems in the HEVC standard are known as Uniform Reconstruction Quantization (URQ) and Rate Distortion Optimized Quantization (RDOQ); URQ and RDOQ are not perceptually optimized for the coding of RGB 4:4:4 video data. In this paper, we propose a novel spatiotemporal perceptual quantization technique named SPAQ. With application for RGB 4:4:4 video data, SPAQ exploits HVS spectral sensitivity-related color masking in addition to spatial masking and temporal masking; SPAQ operates at the Coding Block (CB) level and the Prediction Unit (PU) level. The proposed technique perceptually adjusts the Quantization Step Size (QStep) at the CB level if high variance spatial data in G, B and R CBs is detected and also if high motion vector magnitudes in PUs are detected. Compared with anchor 1 (HEVC HM 16.17 RExt), SPAQ considerably reduces bitrates with a maximum reduction of approximately 80%. The Mean Opinion Score (MOS) in the subjective evaluations, in addition to the SSIM scores, show that SPAQ successfully achieves perceptually lossless compression compared with anchors.

Lee Prangnell

JCT-VC HEVC HM 16 includes a Coding Unit (CU) level adaptive Quantization Parameter (QP) technique named AdaptiveQP. It is designed to perceptually adjust the QP in Y, Cb and Cr Coding Blocks (CBs) based only on the variance of samples in a luma CB. In this paper, we propose an adaptive quantisation technique that consists of two contributions. The first contribution relates to accounting for the variance of chroma samples, in addition to luma samples, in a CU. The second contribution relates to accounting for CU temporal information as well as CU spatial information. Moreover, we integrate into our method a lambda refined QP technique to reduce complexity associated multiple QP optimizations in the Rate Distortion Optimization process. We evaluate the proposed technique on 4:4:4, 4:2:2, 4:2:0 and 4:0:0 YCbCr test sequences, for which we quantify the results using the Bjontegaard Delta Rate (BD-Rate) metric. Our method achieves a maximum BD-Rate reduction of 23.1% (Y), 26.7% (Cr) and 25.2% (Cb). Furthermore, a maximum encoding time reduction of 4.4% is achieved.

Lee Prangnell

The default quantisation algorithms in the state-of-the-art High Efficiency Video Coding (HEVC) standard, namely Uniform Reconstruction Quantisation (URQ) and Rate-Distortion Optimised Quantisation (RDOQ), do not take into account the perceptual relevance of individual transform coefficients. In this paper, a Frequency-Dependent Perceptual Quantisation (FDPQ) technique for HEVC is proposed. FDPQ exploits the well-established Modulation Transfer Function (MTF) characteristics of the linear transformation basis functions by taking into account the Euclidean distance of an AC transform coefficient from the DC coefficient. As such, in luma and chroma Cb and Cr Transform Blocks (TBs), FDPQ quantises more coarsely the least perceptually relevant transform coefficients (i.e., the high frequency AC coefficients). Conversely, FDPQ preserves the integrity of the DC coefficient and the very low frequency AC coefficients. Compared with RDOQ, which is the most widely used transform coefficient-level quantisation technique in video coding, FDPQ successfully achieves bitrate reductions of up to 41%. Furthermore, the subjective evaluations confirm that the FDPQ-coded video data is perceptually indistinguishable (i.e., visually lossless) from the raw video data for a given Quantisation Parameter (QP).

Lee Prangnell, Miguel Hernández-Cabronero, Victor Sanchez

There is an increasing consumer demand for high bit-depth 4:4:4 HD video data playback due to its superior perceptual visual quality compared with standard 8-bit subsampled 4:2:0 video data. Due to vast file sizes and associated bitrates, it is desirable to compress raw high bit-depth 4:4:4 HD video sequences as much as possible without incurring a discernible decrease in visual quality. In this paper, we propose a Coding Block (CB)-level perceptual video coding technique for HEVC named Full Color Perceptual Quantization (FCPQ). FCPQ is designed to adjust the Quantization Parameter (QP) at the CB level (i.e., the luma CB and the chroma Cb and Cr CBs) according to the variances of pixel data in each CB. FCPQ is based on the default perceptual quantization method in HEVC called AdaptiveQP. AdaptiveQP adjusts the QP of an entire CU based only on the spatial activity of the constituent luma CB. As demonstrated in this paper, by not accounting for the spatial activity of the constituent chroma CBs, as is the case with AdaptiveQP, coding performance can be significantly affected; this is because the variance of pixel data in a luma CB is notably different from the variances of pixel data in chroma Cb and Cr CBs. FCPQ, therefore, addresses this problem. In terms of coding performance, FCPQ achieves BD-Rate improvements of up to 39.5% (Y), 16% (Cb) and 29.9% (Cr) compared with AdaptiveQP.

Lee Prangnell, Victor Sanchez

The JCT-VC standardized Screen Content Coding (SCC) extension in the HEVC HM RExt + SCM reference codec offers an impressive coding efficiency performance when compared with HM RExt alone; however, it is not significantly perceptually optimized. For instance, it does not include advanced HVS-based perceptual coding methods, such as JND-based spatiotemporal masking schemes. In this paper, we propose a novel JND-based perceptual video coding technique for HM RExt + SCM. The proposed method is designed to further improve the compression performance of HM RExt + SCM when applied to YCbCr 4:4:4 SC video data. In the proposed technique, luminance masking and chrominance masking are exploited to perceptually adjust the Quantization Step Size (QStep) at the Coding Block (CB) level. Compared with HM RExt 16.10 + SCM 8.0, the proposed method considerably reduces bitrates (Kbps), with a maximum reduction of 48.3%. In addition to this, the subjective evaluations reveal that SC-PAQ achieves visually lossless coding at very low bitrates.

Lee Prangnell

Due to the increasing prevalence of high bit depth and YCbCr 4:4:4 video data, it is desirable to develop a JND-based visually lossless coding technique which can account for high bit depth 4:4:4 data in addition to standard 8-bit precision chroma subsampled data. In this paper, we propose a Coding Block (CB)-level JND-based luma and chroma perceptual quantisation technique for HEVC named Pixel-PAQ. Pixel-PAQ exploits both luminance masking and chrominance masking to achieve JND-based visually lossless coding; the proposed method is compatible with high bit depth YCbCr 4:4:4 video data of any resolution. When applied to YCbCr 4:4:4 high bit depth video data, Pixel-PAQ can achieve vast bitrate reductions, of up to 75% (68.6% over four QP data points), compared with a state-of-the-art luma-based JND method for HEVC named IDSQ. Moreover, the participants in the subjective evaluations confirm that visually lossless coding is successfully achieved by Pixel-PAQ (at a PSNR value of 28.04 dB in one test).

Lee Prangnell, Miguel Hernández-Cabronero, Victor Sanchez

HEVC includes a Coding Unit (CU) level luminance-based perceptual quantization technique known as AdaptiveQP. AdaptiveQP perceptually adjusts the Quantization Parameter (QP) at the CU level based on the spatial activity of raw input video data in a luma Coding Block (CB). In this paper, we propose a novel cross-color channel adaptive quantization scheme which perceptually adjusts the CU level QP according to the spatial activity of raw input video data in the constituent luma and chroma CBs; i.e., the combined spatial activity across all three color channels (the Y, Cb and Cr channels). Our technique is evaluated in HM 16 with 4:4:4, 4:2:2 and 4:2:0 YCbCr JCT-VC test sequences. Both subjective and objective visual quality evaluations are undertaken during which we compare our method with AdaptiveQP. Our technique achieves considerable coding efficiency improvements, with maximum BD-Rate reductions of 15.9% (Y), 13.1% (Cr) and 16.1% (Cb) in addition to a maximum decoding time reduction of 11.0%.

Lee Prangnell, Victor Sanchez

Visual Display Units (VDUs), capable of displaying video data at High Definition (HD) and Ultra HD (UHD) resolutions, are frequently employed in a variety of technological domains. Quantization-induced video compression artifacts, which are usually unnoticeable in low resolution environments, are typically conspicuous on high resolution VDUs and video data. The default quantization matrices (QMs) in HEVC do not take into account specific display resolutions of VDUs or video data to determine the appropriate levels of quantization required to reduce unwanted compression artifacts. Therefore, we propose a novel, adaptive quantization matrix technique for the HEVC standard including Scalable HEVC (SHVC). Our technique, which is based on a refinement of the current QM technique in HEVC, takes into consideration specific display resolutions of the target VDUs in order to minimize compression artifacts. We undertake a thorough evaluation of the proposed technique by utilizing SHVC SHM 9.0 (two-layered bit-stream) and the BD-Rate and SSIM metrics. For the BD-Rate evaluation, the proposed method achieves maximum BD-Rate reductions of 56.5% in the enhancement layer. For the SSIM evaluation, our technique achieves a maximum structural improvement of 0.8660 vs. 0.8538.

Lee Prangnell

There exists a widely accepted set of assertions in the digital image and video coding literature, which are as follows: the Human Visual System (HVS) is more sensitive to luminance (often confused with brightness) than photon energies (often confused with chromaticity and chrominance). Passages similar to the following occur with high frequency in the peer reviewed literature and academic text books: "the HVS is much more sensitive to brightness than colour" and/or "the HVS is much more sensitive to luma than chroma". In this discussion paper, a Visible Light-Based Human Visual System (VL-HVS) conceptual model is discussed. The objectives of VL-HVS are as follows: 1. To provide a deeper theoretical reflection of the fundamental relationship between visible light, the manifestation of colour perception derived from visible light and the physiology of the perception of colour. That is, in terms of the physics of visible light, photobiology and the human subjective interpretation of visible light, it is appropriate to provide comprehensive background information in relation to the natural interactions between visible light, the retinal photoreceptors and the subsequent cortical processing of such. 2. To provide a more wholesome account with respect to colour information in digital image and video processing applications. 3. To recontextualise colour data in the RGB and YCbCr colour spaces, such that novel techniques in digital image and video processing, including quantisation and artifact reduction techniques, may be developed based on both luma and chroma information (not luma data only).

Lee Prangnell, Victor Sanchez

HEVC HM 16 includes a Coding Unit (CU) level perceptual quantization technique named AdaptiveQP. AdaptiveQP adjusts the Quantization Parameter (QP) at the CU level based on the spatial activity of samples in the four constituent NxN sub-blocks of the luma Coding Block (CB), which is contained within a 2Nx2N CU. In this paper, we propose C-BAQ, which, in contrast to AdaptiveQP, adjusts the CU level QP according to the spatial activity of samples in the four constituent NxN sub-blocks of both the luma and chroma CBs. By computing the sum of luma, chroma Cb and chroma Cr spatial activity in a CU, a richer reflection of spatial activity in the CU is attained. Therefore, a more appropriate CU level QP can be selected, thus leading to important improvements in terms of coding efficiency. We evaluate the proposed technique in HEVC HM 16.7 using 4:4:4, 4:2:2 and 4:2:0 YCbCr sequences. Both subjective and objective evaluations are undertaken during which we compare C-BAQ with AdaptiveQP. The objective evaluation reveals that C-BAQ attains a maximum BD-Rate reduction of 15.9% (Y), 13.1% (Cr) and 16.1% (Cb) in addition to a maximum decoding time reduction of 11.0%.