HDR PATCH V2.0
For the earlier versions, HDR-VDP-2 requires matlabPyrTools, which can be downloaded from here. Note that version 1.4 (2009-12-17) of that toolbox contains a bug that prevents HDR-VDP-2 from running. A fixed version of the toolbox can be downloaded from here, or alternatively a MatlabPyrTools patch can be applied to the original toolbox sources.
HDR PATCH V2.0
Download Zip: https://www.google.com/url?q=https%3A%2F%2Fgohhs.com%2F2udFKW&sa=D&sntz=1&usg=AOvVaw31YHSl6HioVrMaen4lGGTy
Worldmerge combines the originally separate world areas of the main campaign, multiplayer maps and Pirates of the Flying Fortress DLC into a unified world with many additions and balance changes. This mod requires the Pirates of the Flying Fortress DLC. Not fully compatible with the latest v2.0+ versions.
God of War Ragnarok patch 2.00 (Day One Patch) details are available for PS4 and PS5(Version 2.000.000). According to God of War Ragnarok update 2.00 patch notes, the day 1 patch update resolves various issues and added gameplay optimizations. Apart from this, God of War Ragnarok version 2.00 also includes stability and performance fixes. The download size is around 800MB.
The game receives positive reviews from critics. It is scheduled to be released worldwide on November 9, 2022, for the PlayStation 4 and PlayStation 5. The God of War Ragnarok day one patch will fix a few issues in the game.
We investigated contextual mechanisms for luminance normalization by testing for interactions between orientation and HDR luminance processing. Previous reports of contextual orientation effects found that flankers drive a facilitating response (making a co-oriented target easier to detect) if the target is low contrast, and this observation was initially attributed to horizontal fibers linking V1 neurons that prefer the same orientation (Ts'o, Gilbert, & Wiesel, 1986). However, at higher contrast, a co-oriented target becomes more difficult to detect than an orthogonal target, an effect that is consistent with suppression of the target visibility or assimilation of the target to surrounding co-oriented patterns, possibly due to feedback from higher pattern-sensitive cortical areas. Both phenomena have also been attributed to the balance of local recurrent excitatory and inhibitory mechanisms in V1, but they have thus far only been investigated for static luminance displays and uniform patch luminance (Chen & Tyler, 2001; Chen & Tyler, 2002; Chen, Kasamatsu, Polat, & Norcia, 2001; Li, 1998; Li, 2011; Polat & Sagi, 1993; Polat & Sagi, 2006; Polat, Mizobe, Pettet, Kasamatsu, & Norcia, 1998).
The target and flanker array consisted of 45 and 135 Gabors, 4 cycles/degree and 1 full width at half maximum Gaussian envelope, cropped to 1 1 and presented on a 5 5 array of 1 1 luminance patches (Figure 2A, top). The spatial frequency of the Gabors is consistent with the stimulus preferences of single neurons in primary visual cortex with receptive fields at 3 eccentricity (Chu, Chien, & Hung, 2014).
Across all blocks, the target was a contrast mixture of two Gabors at 45 (A, tilted right) and 135 (B, tilted left), presented at the central patch at a fixed mean luminance of 4 cd/m2, and subjects indicated via keypress the orientation of the stronger target Gabor. At full contrast (100%), the pixels of each Gabor spanned 3.3 to 0.3 its patch luminance (less than the requested range of 10 to 0.1 patch luminance, due to projector light scatter) (Hung, Callahan-Flintoft, et al., 2020; Hung, Larkin, et al., 2020). The target was shown at one of the five possible A:B contrast mixtures of 70%:30%, 60%:40%, 50%:50%, 40%:60%, or 30%:70%. These contrast mixtures were logarithmically applied to each full-contrast Gabor, such that 50%:50% means that the brightest and darkest pixels of both Gabors are 1.8 and 0.55 the target patch luminance. The five target mixtures were tested in all blocks and conditions. All Gabor patterns were well above the threshold contrast visibility for normal vision. At the minimum average luminance of 0.4 cd/m2, in a field of view 1 by 1, and at a modulation frequency of 4 cycles/degree, Barten (Barten, 2003) reported a minimum visible contrast ratio of 1.03; for a field of view 0.5 by 0.5, the minimum visible contrast ratio increased only to 1.06.
We tested two orthogonalized conditions in which we assigned flankers of interest to different orientation/luminance combinations to determine whether the behavioral biases were driven by the brightest flankers or the flankers that were most similar to the target in luminance. Each 5 5 grid consisted of an inner ring of eight patches and an outer ring of 12 patches. The flankers of interest were balanced within each ring, such that they had the same number of co-oriented and orthogonal flankers, and their locations were spatially balanced in the horizontal and vertical directions to avoid highly asymmetric patterns. In the brightest condition, the flankers of interest were the 12 brightest patches. In the similar luminance condition, the flankers of interest were the 12 patches most similar in luminance to the target patch. For both conditions, we defined flanker condition A as the case in which the Gabor flankers of interest were oriented 45 and the remaining flankers were 135, and vice versa for flanker condition B. The brightest and similar trials were pseudorandomly interleaved within a block.
To understand and model the contextual mechanisms of luminance normalization under real-world luminance dynamics, we introduced two changes to the classic flanker task: (1) a preceding adapting blank background to mimic the luminance change across gaze shifts, and (2) a 5 5 array of luminance patches spanning a 10- or 100-fold difference in luminance to mimic the conjunction of form and luminance in naturalistic scenes. This combination of adapting blanks, patches, and Gabors resulted in a total luminance range of 3333-to-1: 400 cd/m2 for the brightest adapting blank versus 0.12 cd/m2 for the darkest Gabor pixel.
We tested this combination via a two-alternative forced-choice task in which subjects reported the orientation of the stronger of two Gabor targets shown at the center of the 5 5 array (Figure 2A). By fitting the behavioral responses across target contrast mixtures with a psychometric function, we were able to determine whether the flankers induced a facilitatory or suppressive/assimilation effect under real-world luminance dynamics. Additionally, by manipulating the conjunction of patch luminance and patch orientation via two orthogonalized conditions, we were able to test alternative hypotheses about normalization mechanisms that predict whether the brightest flankers or the flankers having a luminance most similar to the target would have stronger effect.
To examine how contextual luminance and orientation combine to affect target discrimination, we manipulated the conjunction of luminance and orientation across the 5 5 array of patches. Figure 2B illustrates schematic examples of such stimuli for the brightest condition in which the flankers of interest (indicated by red lines) are at the brightest patches. In the upper left example of Figure 2B, corresponding to the stimulus example in Figure 2A, the target mixture is 60%/40% and the flanker condition is A, so both the target and the flankers of interest are tilted to the right (45). The comparison condition with the identical target mixture is flanker condition B (lower left), in which the flankers of interest are tilted to the left (135).
Figure 2C (top) illustrates this comparison of orientations for flanker condition A (red open circle, angles above diagonal) versus flanker condition B (blue open circle, angles below diagonal) for the brightest condition, sorted by patch luminance. The red highlights indicate the flankers of interest (the brightest patches in this brightest condition).
In five subjects, we tested two variants of the HDR white block in which we manipulated the degree of luminance variability in the 12 flankers that were nearest in luminance to the target by adjusting them to either the identical luminance as the target (low variability or same, slope 0) or half the original luminance stepping (medium variability or similar, slope 0.5) (Figures 6A and 6B), with the original HDR white condition having high variability (slope 1.0). As in the standard blocks, the positions of the flankers of interest were balanced within each image. Notably, the number of patches and their rules for spatial arrangement were identical between the medium and high luminance variability, and the brightest and darkest luminances remained the same, thus holding constant many factors of concern for lightness theories based on articulation, lightness anchoring, and edge integration (Zemach & Rudd, 2007).
Effect of degree of flanker patch luminance variability. (A) Variants of the HDR white block in which the 12 flankers most similar in luminance to the target were either the same luminance as the target (low luminance variability, slope 0) or at half the original luminance range (medium variability, slope 0.5). Compare with the original luminances (high variability, slope 1, in Figure 2A). The remaining 12 flankers were identical across the three blocks. (B) Patch luminances for low, medium, and high luminance variability, identical for both similar and brightest conditions. (C) Threshold bias effects of similar versus brightest conditions for blocks at low, medium, and high luminance variability. Filled triangles indicate significant effects at p
The results cannot be explained by factors such as contrast-dependent sensitivity of neurons to surround stimuli (Sceniak, Ringach, Hawken, & Shapley, 1999) or retinogeniculate adaptation effects, because these factors were balanced across the brightest and similar conditions. One possibility is that, because the display used in these experiments was considerably more complicated than those in classic flanker studies, including temporal luminance transients and patch edges that do not exist in traditional flanker displays, the spatial frequency energy of the patch edges may have contributed to these effects. Notably, some contemporary theories of lightness (edge integration theories) posit that edges, or more precisely, spatially directed luminance change, may be the signal that the brain uses to compute lightness percepts (Rudd, 2017). Our results are consistent with and expand upon edge integration theories and cannot be explained solely by mechanisms based on divisive normalization. 041b061a72