Manual RenderQualityFlameFractals - Revision history

Thargor6 at 10:48, 21 July 2015

2015-07-21T10:48:33Z

Thargor6: /* Example 10: Fractal with some small artefacts due to sharpening */

2015-07-21T01:58:29Z

‎Example 10: Fractal with some small artefacts due to sharpening

Thargor6: /* Example 8: Fractal with some small artefacts due to sharpening */

2015-07-21T01:58:18Z

‎Example 8: Fractal with some small artefacts due to sharpening

Thargor6: /* Example 9: Artefacts removed by using sample-jittering */

2015-07-21T01:58:07Z

‎Example 9: Artefacts removed by using sample-jittering

Thargor6: /* Example 5: Lanczos filter with radius 1.0 and artefacts */

2015-07-21T01:57:25Z

‎Example 5: Lanczos filter with radius 1.0 and artefacts

Thargor6 at 00:16, 21 July 2015

2015-07-21T00:16:16Z

Thargor6 at 00:11, 21 July 2015

2015-07-21T00:11:48Z

Thargor6: /* Example 12: Softended final image */

2015-07-21T00:08:35Z

‎Example 12: Softended final image

Thargor6 at 00:08, 21 July 2015

2015-07-21T00:08:10Z

Thargor6: /* Post noise-reduction (experimental) */

2015-07-21T00:05:22Z

‎Post noise-reduction (experimental)

@@ Line 21: / Line 21: @@
 When you compare the both images you will see that the 2nd image looks much "brighter" and has more details (You may save them locally for easier comparison, as the differences are not that huge)
-In comparison the "human" method of spatial oversampling the oversampling in JWildfire does oversample the raw data (from the fractal algorithm), not the final image
+In comparison to the "human" method of spatial oversampling, the oversampling in JWildfire does oversample the raw data (from the fractal algorithm), not the final image
 ===Memory usage/render times===

@@ Line 119: / Line 119: @@
 The parameter ''Noise threshold'' controls the contrast of the softened pixels (0: infinite contrast, i. e. no pixel is softened, i.e. effect is turned off; 1: no contrast, i.e. all pixels are softened, i.e. works like a global gaussian filter). The default setting of 0.35 usually leads to a desired effect of softening single pixels of high contrast and leaving the major part of the image untouched.
-==Example 10: Fractal with some small artefacts due to sharpening==
+==Example 10: Fractal with some small artifacts due to sharpening==
 [[File:Chap11_quality_postnoise_off.png]]

@@ Line 105: / Line 105: @@
 This can be done multiple times (parameter ''Color oversampling''), finally the everage of all of this jittered samples is computed.
-==Example 8: Fractal with some small artefacts due to sharpening==
+==Example 8: Fractal with some small artifacts due to sharpening==
 [[File:Chap11_quality_jitter_off.png]]

@@ Line 108: / Line 108: @@
 [[File:Chap11_quality_jitter_off.png]]
-==Example 9: Artefacts removed by using sample-jittering==
+==Example 9: Artifacts removed by using sample-jittering==
 [[File:Chap11_quality_jitter_on.png]]

@@ Line 76: / Line 76: @@
 [[File:Chap11_quality_os2_mitchell1.0.png]]
-===Example 5: Lanczos filter with radius 1.0 and artefacts===
+===Example 5: Lanczos filter with radius 1.0 and artifacts===
 [[File:Chap11_quality_os2_lanczos2_0.9.png]]
 As shown in this example, sometimes a sharpening filter can cause nasty artefacts (i. e. pixels in another color). Sometimes you may defend this by using one of the other options mentioned below, but sometimes you can't just this certain filter for the certain fractal.

← Older revision		Revision as of 00:16, 21 July 2015
Line 129:		Line 129:

	This feature is experimental and my change in the future.		This feature is experimental and my change in the future.
		+
		+	=Customizing initial values=
		+	You may customize the initial values of all of this options to your needs by using the Preferences.
		+	There are the following properties you may change (a short description is supplied in the window itself, so I will not explain them here):
		+	#tinaDefaultAntialiasingAmount
		+	#tinaDefaultAntialiasingRadius
		+	#tinaDefaultColorOversampling
		+	#tinaDefaultPostNoiseFilter
		+	#tinaDefaultPostNoiseFilterThreshold
		+	#tinaDefaultSpatialFilterKernel
		+	#tinaDefaultSpatialFilterRadius
		+	#tinaDefaultSpatialOversampling

@@ Line 9: / Line 9: @@
 [[File:Chap11_quality_options.jpg]]
-==Spatial oversampling==
+=Spatial oversampling=
 Spatial oversampling is probably the most powerful tool to increase the level of detail of your fractals.
 It works in a similar way as many artists also create their digital images: they create their image at higher resolution and scale it finally down using some clever algorithm/software. The result usually looks better than it would have, when created at the original size.
 The spatial-oversampling-setting in JWildfire is an integer setting. A value of 1 means to render internally at original size, a value of 2 to render at double size, etc.
-===Example 1: Spatial oversampling 1 (raw, without any antialiasing)===
+==Example 1: Spatial oversampling 1 (raw, without any antialiasing)==
 [[File:Chap11_quality_oversample1.png]]<br>
-===Example 2: Spatial oversampling 2 (raw, without any antialiasing)===
+==Example 2: Spatial oversampling 2 (raw, without any antialiasing)==
 [[File:Chap11_quality_oversample2.png]]<br>
 When you compare the both images you will see that the 2nd image looks much "brighter" and has more details (You may save them locally for easier comparison, as the differences are not that huge)
@@ Line 31: / Line 31: @@
 #Spatial oversample 3: memory-usage 9 times as much, render time three times as long
-==Spatial filtering==
+=Spatial filtering=
 Spatial oversampling opens the door to some other nice and powerful feature: the spatial filtering. In the previous paragraph we saw that in spatial oversampling several samples are calculated to generate one final point of the image. But we did not see how this is done.
-===Simplest approach===
+==Simplest approach==
 The simplest approach is to calculate the average of samples generated for each pixel, and use this average as final value.
 E.g., when using spatial oversampling of 2, we calculate 4 raw samples per pixel, and use the average of this 4 samples to generate one pixel.
 Also this simple approach is some kind of spatial filtering: applying some formula to a number of samples in the neighborhood of the final pixel (using a box-filter in this example).
-===Spatial filter kernels===
+==Spatial filter kernels==
 The ''formula'' applied in spatial filtering is called a filter kernel. JWildfire currently has 14 included filter-kernels. While they often differ only slightly in shape, they may have a huge impact.<br>
 [[File:Chap11_filter_kernels.jpg]]
-====Spatial filter radius====
+==Spatial filter radius==
 The filter radius specifies the size of the zone around the centre of a raw sample which is taken into account to calculate one final pixel.
 As a rule of thumb: the larger this zone, the smoother the image, the more time it takes, and the less details you finally have.
-====Filter kernel preview====
+===Filter kernel preview===
 To help you to choose the right filter and filter radius JWildfire offers a preview of the filter kernel.
 There are both a 3d or 2d-preview. While the 3d-preview is prettier, it may be slow on older machines, so you may also chose to have a flat preview. (You can change your preference in the Preference-window by changing the property ''tinaDefaultFilterVisualisationFlat'')
-=====Filter kernel preview in 3D=====
+====Filter kernel preview in 3D====
 This view shows a grid of cubuids, each one representing a sample. The center cubuid is the center sample.
 The higher each cubuid, the higher is the influence of the sample on the final pixel. Usually, the center cubuid has the largest hight, i. e., the highes influence.<br>
@@ Line 59: / Line 59: @@
 [[File:Chap11_kernel_preview_3d_lanczos2.jpg]]<br>
-=====Filter kernel preview in 2D=====
+====Filter kernel preview in 2D====
 The 2D-preview is faster but can not visualize the shape of the filter kernel as clear as the 3d-view.
 It displays the cubuids from a top view. Brighter areas are "higher" areas, i.e. samples with high influence, and dark parts are samples with low influence.<br>
@@ Line 67: / Line 67: @@
 [[File:Chap11_kernel_preview_2d_lanczos2.jpg]]
-===Sharpening/Soften filters===
+==Sharpening/Soften filters==
 As a general rule of thumb: filter kernels with negative (red) parts are sharpening details, while filters with only positive parts are softening.
-====Example 3: Gaussian filter with radius 1.0====
+===Example 3: Gaussian filter with radius 1.0===
 [[File:Chap11_quality_os2_gaussian1.0.png]]
-====Example 4: Mitchell filter with radius 1.0====
+===Example 4: Mitchell filter with radius 1.0===
 [[File:Chap11_quality_os2_mitchell1.0.png]]
-====Example 5: Lanczos filter with radius 1.0 and artefacts====
+===Example 5: Lanczos filter with radius 1.0 and artefacts===
 [[File:Chap11_quality_os2_lanczos2_0.9.png]]
 As shown in this example, sometimes a sharpening filter can cause nasty artefacts (i. e. pixels in another color). Sometimes you may defend this by using one of the other options mentioned below, but sometimes you can't just this certain filter for the certain fractal.
-==Anti-aliasing==
+=Anti-aliasing=
 When your fractal shows jagged edges you can get rid of them by using the anti-aliasing-settings.
-===Example 6: Fractal without anti-aliasing and without oversampling===
+==Example 6: Fractal without anti-aliasing and without oversampling==
 [[File:Chap11_antialias_off.png]]
@@ Line 93: / Line 93: @@
 But, please be beware, that antialiasing may reduce details and does wash out colors when overused, so use with care.
-===Example 7: Fractal with anti-aliasing (without oversampling)===
+==Example 7: Fractal with anti-aliasing (without oversampling)==
 [[File:Chap11_antialias_on.png]]
-==Sample-jittering (experimental)==
+=Sample-jittering (experimental)=
 The idea behind sample-jittering is to reduce artifacts, jaggy lines or noise by adding some random behaviour (multipy times).
 Usually, when calculating a pixel from sample values (using a filter-kernel) each sample is taken as it is.<br>
@@ Line 105: / Line 105: @@
 This can be done multiple times (parameter ''Color oversampling''), finally the everage of all of this jittered samples is computed.
-===Example 8: Fractal with some small artefacts due to sharpening===
+==Example 8: Fractal with some small artefacts due to sharpening==
 [[File:Chap11_quality_jitter_off.png]]
-===Example 9: Artefacts removed by using sample-jittering===
+==Example 9: Artefacts removed by using sample-jittering==
 [[File:Chap11_quality_jitter_on.png]]
 This feature is experimental and my change in the future.
-==Post noise-reduction (experimental)==
+=Post noise-reduction (experimental)=
 All the options described before, work on the raw samples generated by the flame-fractal-algorithm and apply to the buffer specified by spatial-oversampling-setting.
 But, there is one more filter-option, which applies to the already generated image.
@@ Line 119: / Line 119: @@
 The parameter ''Noise threshold'' controls the contrast of the softened pixels (0: infinite contrast, i. e. no pixel is softened, i.e. effect is turned off; 1: no contrast, i.e. all pixels are softened, i.e. works like a global gaussian filter). The default setting of 0.35 usually leads to a desired effect of softening single pixels of high contrast and leaving the major part of the image untouched.
-===Example 10: Fractal with some small artefacts due to sharpening===
+==Example 10: Fractal with some small artefacts due to sharpening==
 [[File:Chap11_quality_postnoise_off.png]]
-===Example 11: Pixels of high contrast seen by the post-noise-filter===
+==Example 11: Pixels of high contrast seen by the post-noise-filter==
 [[File:Chap11_quality_postnoise_debug.png]]
-===Example 12: Softened final image===
+==Example 12: Softened final image==
 [[File:Chap11_quality_postnoise_on.png]]
 This feature is experimental and my change in the future.