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https://github.com/bspeice/speice.io
synced 2024-12-22 00:28:10 -05:00
More writing. Hopefully can finish the first draft soon
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@ -243,8 +243,8 @@ This allows us to manipulate individual pixels an image,
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and display it on screen.
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First, we need to convert from Fractal Flame coordinates to pixel coordinates.
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To simplify things, we'll assume that we're plotting a square image,
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and we'll focus on the range $[0, 1]$ for both $x$ and $y$:
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To simplify things, we'll assume that we're plotting a square image
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with range $[0, 1]$ for both $x$ and $y$:
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import cameraSource from "!!raw-loader!./cameraGasket"
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@ -13,7 +13,7 @@ type PaletteBarProps = {
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palette: number[];
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children?: React.ReactNode;
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}
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const PaletteBar: React.FC<PaletteBarProps> = ({height, palette, children}) => {
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export const PaletteBar: React.FC<PaletteBarProps> = ({height, palette, children}) => {
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const sizingRef = useRef<HTMLDivElement>(null);
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const [width, setWidth] = useState(0);
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useEffect(() => {
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@ -51,10 +51,12 @@ const PaletteBar: React.FC<PaletteBarProps> = ({height, palette, children}) => {
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}
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}, [canvasRef, paletteImage]);
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const canvasStyle = {filter: useColorMode().colorMode === 'dark' ? 'invert(1)' : ''};
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return (
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<>
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<div ref={sizingRef} style={{width: '100%', height}}>
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{width > 0 ? <canvas ref={canvasRef} width={width} height={height}/> : null}
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{width > 0 ? <canvas ref={canvasRef} width={width} height={height} style={canvasStyle}/> : null}
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</div>
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{children}
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</>
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@ -6,13 +6,11 @@ authors: [bspeice]
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tags: []
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---
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So far, our `plot()` function has been fairly simple; map an input coordinate
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to a specific pixel, and color in that pixel.
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This works well for simple function systems (like Sierpinski's Gasket),
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So far, our `plot()` function has been fairly simple; map an input coordinate to a specific pixel,
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and color in that pixel. This works well for simple function systems (like Sierpinski's Gasket),
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but more complex systems (like our reference parameters) produce grainy images.
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Every additional time we plot a pixel, we're wasting work.
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Can we do something more intelligent instead?
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In this post, we'll refine the image quality and add color to really make things shine.
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<!-- truncate -->
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@ -22,13 +20,14 @@ Can we do something more intelligent instead?
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This post covers sections 4 and 5 of the Fractal Flame Algorithm paper
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:::
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To start with, it's worth demonstrating how much work is actually "wasted."
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Previously, pixels would be either transparent or opaque depending on whether
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we encountered them while running the chaos game.
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To start, it's worth demonstrating how much work is actually "wasted"
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when we treat pixels as a binary "on" (opaque) or "off" (transparent).
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We'll render the reference image again, but this time, keep track of how many times
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we encounter each pixel during the chaos game. At the end, we'll "paint" our final image
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by setting each pixel's transparency based on how frequently we encounter it:
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We'll render the reference image again, but this time, track each time
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we encounter each pixel during the chaos game. When the chaos game finishes,
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find the pixel we encountered most frequently. Finally, "paint" the image
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by setting each pixel's transparency to ratio of times encountered
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divided by the maximum value:
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import CodeBlock from "@theme/CodeBlock";
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@ -40,27 +39,40 @@ import {SquareCanvas} from "../src/Canvas";
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import FlameHistogram from "./FlameHistogram";
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import {paintLinear} from "./paintLinear";
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<SquareCanvas><FlameHistogram quality={5} paint={paintLinear}/></SquareCanvas>
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<SquareCanvas><FlameHistogram quality={15} paint={paintLinear}/></SquareCanvas>
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## Log display
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Using a histogram to paint our image is definitely a quality improvement,
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but it produces "ghostly" images. In our reference parameters, the outer circle
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While using a histogram to paint the image improves the quality,
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it also leads to some parts vanishing entirely.
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In the reference parameters, the outer circle
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is preserved, but the interior appears to be missing!
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To fix this, we'll introduce the second major innovation of the fractal flame algorithm: tone mapping.
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This technique is used in computer graphics to adjust for the fact that
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people perceive brightness on a logarithmic scale.
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To fix this, we'll introduce the second major innovation of the fractal flame algorithm: [tone mapping](https://en.wikipedia.org/wiki/Tone_mapping).
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This is a technique used in computer graphics to compensate for differences in how
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computers represent color, and how color is perceived by people.
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As a concrete example, high dynamic range (HDR) photography uses this technique to capture
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nice images of scenes with very different brightness levels. If you want to take a picture of something dark,
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you need a long exposure time. However, long exposures lead to bright spots that "wash out" and become nothing but white.
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If we take multiple images using different exposure times, we can blend them together to create
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nice images of scenes with wide brightness ranges. To take a picture of something dark,
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you need a long exposure time. However, long exposures can lead to images that "wash out" and become pure white.
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By taking multiple pictures using different exposure times, we can combine them to create
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a final image where everything is visible.
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TODO: HDR link?
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In fractal flames, this "tone map" is accomplished by scaling brightness according to the _logarithm_
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of how many times we encounter a pixel. This way, "dark spots" (pixels the chaos game visits infrequently)
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will still be visible, and "bright spots" (pixels the chaos game visits frequently) won't wash out.
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In fractal flames, this "tone map" is accomplished
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<details>
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<summary>Log-scale vibrancy is also why fractal flames appear to be 3D...</summary>
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As explained in the Fractal Flame paper:
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> Where one branch of the fractal crosses another, one may appear to occlude the other
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> if their densities are different enough because the lesser density is inconsequential in sum.
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> For example, branches of densities 1000 and 100 might have brightnesses of 30 and 20.
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> Where they cross the density is 1100, whose brightness is 30.4, which is
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> hardly distinguishable from 30.
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</details>
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import paintLogarithmicSource from "!!raw-loader!./paintLogarithmic"
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@ -68,10 +80,29 @@ import paintLogarithmicSource from "!!raw-loader!./paintLogarithmic"
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import {paintLogarithmic} from './paintLogarithmic'
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<SquareCanvas><FlameHistogram quality={10} paint={paintLogarithmic}/></SquareCanvas>
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<SquareCanvas><FlameHistogram quality={15} paint={paintLogarithmic}/></SquareCanvas>
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## Color
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Finally, we'll spice things up with the last innovation introduced by
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the fractal flame algorithm: color. By including a color coordinate
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in the chaos game, we can illustrate the transforms that are responsible
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for each part of an image.
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### Palette
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Our first step is to define a color palette for the image. Fractal flames
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typically use a palette of 256 colors that transition smoothly
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from one to another. In the diagram below, each color in our palette is plotted
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on a small strip. Putting the strips side by side shows the palette for our image:
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import * as params from "../src/params"
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import {PaletteBar} from "./FlameColor"
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<PaletteBar height="40" palette={params.palette}/>
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### Color coordinate
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import paintColorSource from "!!raw-loader!./paintColor"
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<CodeBlock language="typescript">{paintColorSource}</CodeBlock>
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@ -1,7 +1,7 @@
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export function paintLogarithmic(width: number, height: number, histogram: number[]): ImageData {
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const image = new ImageData(width, height);
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const histogramLog = new Array<number>();
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const histogramLog: number[] = [];
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histogram.forEach(value => histogramLog.push(Math.log(value)));
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let histogramLogMax = -Infinity;
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@ -1,4 +1,4 @@
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import React, {useEffect, useState, createContext, useRef} from "react";
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import React, {useEffect, useState, createContext, useRef, MouseEvent} from "react";
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import {useColorMode} from "@docusaurus/theme-common";
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type PainterProps = {
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@ -8,6 +8,13 @@ type PainterProps = {
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}
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export const PainterContext = createContext<PainterProps>(null)
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const downloadImage = (e: MouseEvent) => {
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const link = document.createElement("a");
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link.download = "flame.png";
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link.href = (e.target as HTMLCanvasElement).toDataURL("image/png");
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link.click();
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}
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type CanvasProps = {
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style?: any;
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children?: React.ReactElement
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@ -86,7 +93,7 @@ export const Canvas: React.FC<CanvasProps> = ({style, children}) => {
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<>
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<center>
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<div ref={sizingRef} style={style}>
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{width > 0 ? <canvas {...canvasProps}/> : null}
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{width > 0 ? <canvas {...canvasProps} onDoubleClick={downloadImage}/> : null}
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</div>
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</center>
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<PainterContext.Provider value={{width, height, setPainter}}>
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@ -99,11 +99,8 @@ const config: Config = {
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plugins: [require.resolve('docusaurus-lunr-search')],
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stylesheets: [
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{
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href: 'https://cdn.jsdelivr.net/npm/katex@0.13.24/dist/katex.min.css',
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href: '/katex/katex.min.css',
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type: 'text/css',
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integrity:
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'sha384-odtC+0UGzzFL/6PNoE8rX/SPcQDXBJ+uRepguP4QkPCm2LBxH3FA3y+fKSiJ+AmM',
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crossorigin: 'anonymous',
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},
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],
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future: {
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