Android Bitmap 模糊效果实现 (二)

Android Bitmap 模糊效果实现 (二)

本文首发地址 https://blog.csdn.net/CSqingchen/article/details/134656140
最新更新地址 https://gitee.com/chenjim/chenjimblog

通过 Android Bitmap 模糊效果实现 (一)，我们知道可以使用 Toolkit 实现 Bitmap 模糊，还能达到不错的效果。本文主要讲解另外几种实现Bitmap模糊的方法并对比效率。

使用 Vukan 模糊

Vulkan 是一种低开销、跨平台的 API，用于高性能 3D 图形。
Android平台包含 Khronos Group 的 Vulkan API规范的特定实现。
Android Vulkan 使用可以参考：
https://developer.android.com/ndk/guides/graphics/getting-started

使用 Vukan 模糊的核心代码如下，可参考 ImageProcessor.cpp

bool ImageProcessor::blur(float radius, int outputIndex) {
    RET_CHECK(1.0f <= radius && radius <= 25.0f);

    // Calculate gaussian kernel, this is equivalent to ComputeGaussianWeights at
    // https://cs.android.com/android/platform/superproject/+/master:frameworks/rs/cpu_ref/rsCpuIntrinsicBlur.cpp;l=57
    constexpr float e = 2.718281828459045f;
    constexpr float pi = 3.1415926535897932f;
    float sigma = 0.4f * radius + 0.6f;
    float coeff1 = 1.0f / (std::sqrtf(2.0f * pi) * sigma);
    float coeff2 = -1.0f / (2.0f * sigma * sigma);
    int32_t iRadius = static_cast<int>(std::ceilf(radius));
    float normalizeFactor = 0.0f;
    for (int r = -iRadius; r <= iRadius; r++) {
        const float value = coeff1 * std::powf(e, coeff2 * static_cast<float>(r * r));
        mBlurData.kernel[r + iRadius] = value;
        normalizeFactor += value;
    }
    normalizeFactor = 1.0f / normalizeFactor;
    for (int r = -iRadius; r <= iRadius; r++) {
        mBlurData.kernel[r + iRadius] *= normalizeFactor;
    }
    RET_CHECK(mBlurUniformBuffer->copyFrom(&mBlurData));

    // Apply a two-pass blur algorithm: a horizontal blur kernel followed by a vertical
    // blur kernel. This is equivalent to, but more efficient than applying a 2D blur
    // filter in a single pass. The two-pass blur algorithm has two kernels, each of
    // time complexity O(iRadius), while the single-pass algorithm has only one kernel,
    // but the time complexity is O(iRadius^2).
    auto cmd = mCommandBuffer->handle();
    RET_CHECK(beginOneTimeCommandBuffer(cmd));

    // The temp image is used as an output storage image in the first pass.
    mTempImage->recordLayoutTransitionBarrier(cmd, VK_IMAGE_LAYOUT_GENERAL, /*preserveData=*/false);

    // First pass: apply a horizontal gaussian blur.
    mBlurHorizontalPipeline->recordComputeCommands(cmd, &iRadius, *mInputImage, *mTempImage,
                                                   mBlurUniformBuffer.get());

    // The temp image is used as an input sampled image in the second pass,
    // and the staging image is used as an output storage image.
    mTempImage->recordLayoutTransitionBarrier(cmd, VK_IMAGE_LAYOUT_SHADER_READ_ONLY_OPTIMAL);
    mStagingOutputImage->recordLayoutTransitionBarrier(cmd, VK_IMAGE_LAYOUT_GENERAL,
                                                       /*preserveData=*/false);

    // Second pass: apply a vertical gaussian blur.
    mBlurVerticalPipeline->recordComputeCommands(cmd, &iRadius, *mTempImage, *mStagingOutputImage,
                                                 mBlurUniformBuffer.get());

    // Prepare for image copying from the staging image to the output image.
    mStagingOutputImage->recordLayoutTransitionBarrier(cmd, VK_IMAGE_LAYOUT_TRANSFER_SRC_OPTIMAL);

    // Copy staging image to output image.
    recordImageCopyingCommand(cmd, *mStagingOutputImage, *mOutputImages[outputIndex]);

    // Submit to queue.
    RET_CHECK(endAndSubmitCommandBuffer(cmd, mContext->queue()));
    return true;
}

Vukan 环境、资源、Pipeline 相关代码如下

https://github.com/android/renderscript-samples/tree/main/RenderScriptMigrationSample/app/src/main/cpp

上层接口参见 VulkanImageProcessor

这里需要用到 libVkLayer_khronos_validation.so， 可以在以下地址下载新版本
https://github.com/KhronosGroup/Vulkan-ValidationLayers

使用 RenderEffect 模糊

实现代码如下

override fun blur(radius: Float, outputIndex: Int): Bitmap {
    params?.let {
        val blurRenderEffect = RenderEffect.createBlurEffect(
            radius, radius,
            Shader.TileMode.MIRROR
        )
        return applyEffect(it, blurRenderEffect, outputIndex)
    }
    throw RuntimeException("Not configured!")
}
private fun applyEffect(it: Params, renderEffect: RenderEffect, outputIndex: Int): Bitmap {
    it.renderNode.setRenderEffect(renderEffect)
    val renderCanvas = it.renderNode.beginRecording()
    renderCanvas.drawBitmap(it.bitmap, 0f, 0f, null)
    it.renderNode.endRecording()
    it.hardwareRenderer.createRenderRequest()
        .setWaitForPresent(true)
        .syncAndDraw()

    val image = it.imageReader.acquireNextImage() ?: throw RuntimeException("No Image")
    val hardwareBuffer = image.hardwareBuffer ?: throw RuntimeException("No HardwareBuffer")
    val bitmap = Bitmap.wrapHardwareBuffer(hardwareBuffer, null)
        ?: throw RuntimeException("Create Bitmap Failed")
    hardwareBuffer.close()
    image.close()
    return bitmap
}
inner class Params(val bitmap: Bitmap, numberOfOutputImages: Int) {
    @SuppressLint("WrongConstant")
    val imageReader = ImageReader.newInstance(
        bitmap.width, bitmap.height,
        PixelFormat.RGBA_8888, numberOfOutputImages,
        HardwareBuffer.USAGE_GPU_SAMPLED_IMAGE or HardwareBuffer.USAGE_GPU_COLOR_OUTPUT
    )
    val renderNode = RenderNode("RenderEffect")
    val hardwareRenderer = HardwareRenderer()

    init {
        hardwareRenderer.setSurface(imageReader.surface)
        hardwareRenderer.setContentRoot(renderNode)
        renderNode.setPosition(0, 0, imageReader.width, imageReader.height)
    }
}

完整实例参考
RenderEffectImageProcessor.kt

使用 GLSL 模糊

主要流程：

• 将输入 Bitmap 转为纹理
  GLES31.glTexStorage2D( GLES31.GL_TEXTURE_2D, 1, GLES31.GL_RGBA8, mInputImage.width, mInputImage.height )
• 通过 OpenGL 处理纹理

完整实例参考 GLSLImageProcessor.kt

RS、Vukan、RenderEffect、GLSL 效率对比

通过示例 RenderScriptMigrationSample 可以看到
他们之间效率对比结果如下

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以上就是 Bitmap 模糊实现的方案二，希望对你有所帮助。
如果你在使用过程遇到问题，可以留言讨论。
如果你觉得本文写的还不错，欢迎点赞收藏。

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