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// Java 层入口
public final class Bitmap {
    public boolean compress(CompressFormat format, int quality, OutputStream stream) {
        // 参数校验
        checkRecycled("Can't compress a recycled bitmap");
        if (stream == null) {
            throw new NullPointerException();
        }
        if (quality < 0 || quality > 100) {
            throw new IllegalArgumentException("quality must be 0..100");
        }
        
        // 调用 Native 方法
        return nativeCompress(mNativePtr, format.nativeInt, quality, stream,
                             new byte[WORKING_COMPRESS_STORAGE]);
    }
}

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Bitmap.compress()
    ↓
JNI: Bitmap_compress() [android_graphics_Bitmap.cpp]
    ↓
SkEncodeImage() [SkImageEncoder.cpp]
    ↓
根据格式选择编码器：
    ├─ SkJpegEncoder::Encode()
    ├─ SkPngEncoder::Encode()
    └─ SkWebpEncoder::Encode()

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// frameworks/base/libs/hwui/jni/Bitmap.cpp
static jboolean Bitmap_compress(JNIEnv* env, jobject clazz,
                                 jlong bitmapHandle, jint format, jint quality,
                                 jobject jstream, jbyteArray jstorage) {
    
    // 1. 获取 Bitmap 对象
    Bitmap* bitmap = reinterpret_cast<Bitmap*>(bitmapHandle);
    SkBitmap skBitmap;
    bitmap->getSkBitmap(&skBitmap);
    
    // 2. 创建输出流包装器
    SkWStream* strm = CreateJavaOutputStreamAdaptor(env, jstream, jstorage);
    
    // 3. 根据格式选择编码器
    SkEncodedImageFormat encodedFormat;
    switch (format) {
        case kJPEG_JavaEncodeFormat:
            encodedFormat = SkEncodedImageFormat::kJPEG;
            break;
        case kPNG_JavaEncodeFormat:
            encodedFormat = SkEncodedImageFormat::kPNG;
            break;
        case kWEBP_JavaEncodeFormat:
            encodedFormat = SkEncodedImageFormat::kWEBP;
            break;
        default:
            return JNI_FALSE;
    }
    
    // 4. 执行编码
    SkPixmap pixmap;
    if (!skBitmap.peekPixels(&pixmap)) {
        return JNI_FALSE;
    }
    
    return SkEncodeImage(strm, pixmap, encodedFormat, quality);
}

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// external/skia/src/encode/SkJpegEncoder.cpp
bool SkJpegEncoder::Encode(SkWStream* dst, const SkPixmap& src, const Options& options) {
    // 1. 初始化 libjpeg
    jpeg_compress_struct cinfo;
    jpeg_error_mgr jerr;
    cinfo.err = jpeg_std_error(&jerr);
    jpeg_create_compress(&cinfo);
    
    // 2. 设置目标流
    SkJpegStream jpegStream(dst);
    jpeg_set_stream(&cinfo, &jpegStream);
    
    // 3. 配置压缩参数
    cinfo.image_width = src.width();
    cinfo.image_height = src.height();
    cinfo.input_components = 3; // RGB
    cinfo.in_color_space = JCS_RGB;
    
    jpeg_set_defaults(&cinfo);
    jpeg_set_quality(&cinfo, options.fQuality, TRUE);
    
    // 4. 色彩空间转换
    if (src.colorType() == kRGBA_8888_SkColorType) {
        // RGBA → RGB 转换（丢弃 Alpha）
        convert_RGBA_to_RGB(src, rgb_buffer);
    }
    
    // 5. 开始压缩
    jpeg_start_compress(&cinfo, TRUE);
    
    // 6. 逐行编码
    while (cinfo.next_scanline < cinfo.image_height) {
        JSAMPROW row_pointer = (JSAMPROW)&rgb_buffer[cinfo.next_scanline * row_stride];
        jpeg_write_scanlines(&cinfo, &row_pointer, 1);
    }
    
    // 7. 完成压缩
    jpeg_finish_compress(&cinfo);
    jpeg_destroy_compress(&cinfo);
    
    return true;
}

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public class EncodingBenchmark {
    
    public void benchmarkEncodingFormats(Bitmap bitmap) {
        // 测试配置
        int[] qualities = {50, 75, 90};
        CompressFormat[] formats = {
            CompressFormat.JPEG,
            CompressFormat.PNG,
            CompressFormat.WEBP
        };
        
        for (CompressFormat format : formats) {
            for (int quality : qualities) {
                long startTime = System.nanoTime();
                
                ByteArrayOutputStream baos = new ByteArrayOutputStream();
                bitmap.compress(format, quality, baos);
                
                long duration = (System.nanoTime() - startTime) / 1_000_000; // ms
                int size = baos.size() / 1024; // KB
                
                Log.d("Benchmark", String.format(
                    "%s Q%d: %dms, %dKB",
                    format.name(), quality, duration, size
                ));
            }
        }
    }
}

// 实测结果（Pixel 6 Pro）:
// JPEG Q50:  45ms, 178KB
// JPEG Q75:  52ms, 312KB  ← 推荐配置
// JPEG Q90:  68ms, 521KB
//
// PNG  Q50:  120ms, 1024KB ← quality 参数无效
// PNG  Q75:  118ms, 1024KB
// PNG  Q90:  121ms, 1024KB
//
// WEBP Q50:  95ms, 156KB
// WEBP Q75:  108ms, 245KB  ← 最佳性价比
// WEBP Q90:  142ms, 389KB

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def calculate_quantization_table(quality):
    """
    计算 JPEG 量化表
    基于 IJG (Independent JPEG Group) 算法
    """
    # IJG 标准量化表（quality=50）
    Q50 = [
        [16, 11, 10, 16, 24, 40, 51, 61],
        [12, 12, 14, 19, 26, 58, 60, 55],
        [14, 13, 16, 24, 40, 57, 69, 56],
        [14, 17, 22, 29, 51, 87, 80, 62],
        [18, 22, 37, 56, 68, 109, 103, 77],
        [24, 35, 55, 64, 81, 104, 113, 92],
        [49, 64, 78, 87, 103, 121, 120, 101],
        [72, 92, 95, 98, 112, 100, 103, 99]
    ]
    
    # Quality 转换为缩放因子
    if quality < 50:
        scale = 5000 / quality
    else:
        scale = 200 - quality * 2
    
    # 缩放量化表
    Q_table = []
    for row in Q50:
        scaled_row = []
        for val in row:
            scaled_val = (val * scale + 50) // 100
            scaled_val = max(1, min(255, scaled_val))  # 限制范围
            scaled_row.append(scaled_val)
        Q_table.append(scaled_row)
    
    return Q_table

# 示例输出
print("Quality=10:")
print(calculate_quantization_table(10))
# [[80, 55, 50, 80, 120, 200, 255, 255], ...]  ← 激进量化

print("\nQuality=75:")
print(calculate_quantization_table(75))
# [[ 8,  6,  5,  8, 12, 20, 26, 31], ...]  ← 平衡量化

print("\nQuality=95:")
print(calculate_quantization_table(95))
# [[ 2,  1,  1,  2,  2,  4,  5,  6], ...]  ← 保守量化

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public class AdaptiveQualitySelector {
    
    /**
     * 根据图像特征自动选择最佳 Quality
     */
    public int selectOptimalQuality(Bitmap bitmap, int targetSizeKB) {
        // 1. 二分查找最佳 quality
        int low = 10, high = 95;
        int bestQuality = 75;
        
        while (low <= high) {
            int mid = (low + high) / 2;
            int actualSize = estimateCompressedSize(bitmap, mid);
            
            if (actualSize <= targetSizeKB * 1024) {
                bestQuality = mid;
                low = mid + 1; // 尝试更高质量
            } else {
                high = mid - 1; // 降低质量
            }
        }
        
        return bestQuality;
    }
    
    /**
     * 估算压缩后大小（快速预测，无需实际编码）
     */
    private int estimateCompressedSize(Bitmap bitmap, int quality) {
        int pixels = bitmap.getWidth() * bitmap.getHeight();
        int complexity = calculateComplexity(bitmap);
        
        // 经验公式（基于大量测试数据拟合）
        // 复杂度越高，压缩率越低
        double compressionRatio = 0.01 + (quality / 100.0) * 0.15 + (complexity / 1000.0) * 0.05;
        
        return (int) (pixels * 4 * compressionRatio);
    }
    
    private int calculateComplexity(Bitmap bitmap) {
        // 使用梯度密度评估复杂度（参考进阶篇）
        int width = bitmap.getWidth();
        int height = bitmap.getHeight();
        int edgeCount = 0;
        
        // 采样检测（避免全图扫描）
        int step = 10;
        for (int y = 0; y < height; y += step) {
            for (int x = 0; x < width; x += step) {
                if (x + 1 < width && y + 1 < height) {
                    int center = bitmap.getPixel(x, y);
                    int right = bitmap.getPixel(x + 1, y);
                    int bottom = bitmap.getPixel(x, y + 1);
                    
                    if (colorDistance(center, right) > 30 ||
                        colorDistance(center, bottom) > 30) {
                        edgeCount++;
                    }
                }
            }
        }
        
        return edgeCount;
    }
    
    private int colorDistance(int color1, int color2) {
        int r1 = Color.red(color1), g1 = Color.green(color1), b1 = Color.blue(color1);
        int r2 = Color.red(color2), g2 = Color.green(color2), b2 = Color.blue(color2);
        
        // 欧几里得距离
        return (int) Math.sqrt(
            Math.pow(r1 - r2, 2) + Math.pow(g1 - g2, 2) + Math.pow(b1 - b2, 2)
        );
    }
}

// 使用示例
AdaptiveQualitySelector selector = new AdaptiveQualitySelector();
int quality = selector.selectOptimalQuality(bitmap, 200); // 目标 200KB
bitmap.compress(CompressFormat.JPEG, quality, outputStream);

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public class ProgressiveJpegEncoder {
    
    /**
     * Android 默认不支持渐进式 JPEG，需自定义实现
     */
    public void encodeProgressiveJpeg(Bitmap bitmap, File outputFile, int quality) 
            throws IOException {
        
        // 使用第三方库（如 libjpeg-turbo）
        TurboJpegEncoder encoder = new TurboJpegEncoder();
        encoder.setQuality(quality);
        encoder.setProgressive(true); // 启用渐进式
        encoder.encode(bitmap, outputFile);
    }
}

// 渐进式 JPEG 优势：
// 1. 快速显示低质量预览
// 2. 逐步提升清晰度
// 3. 用户体验更好（网络图片加载）
//
// 劣势：
// 1. 文件略大（+2-3%）
// 2. 编码时间稍长（+10%）
// 3. 解码内存占用更高

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public class WebpQualityGuide {
    
    /**
     * WEBP quality 参数的特殊含义
     */
    public void demonstrateWebpQuality(Bitmap bitmap) throws IOException {
        // 1. quality < 100: 有损模式
        ByteArrayOutputStream lossy = new ByteArrayOutputStream();
        bitmap.compress(CompressFormat.WEBP, 80, lossy);
        
        // 2. quality == 100: 无损模式（Android 9.0+）
        if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.P) {
            ByteArrayOutputStream lossless = new ByteArrayOutputStream();
            bitmap.compress(CompressFormat.WEBP, 100, lossless);
            
            Log.d("WEBP", "Lossy size: " + lossy.size());
            Log.d("WEBP", "Lossless size: " + lossless.size());
            // Lossless 通常是 Lossy 的 2-3 倍大
        }
    }
    
    /**
     * 推荐的 WEBP 质量参数
     */
    public int getRecommendedWebpQuality(ImageType type) {
        switch (type) {
            case PHOTO:
                return 75; // 照片：平衡质量与体积
            case ICON:
                return 100; // 图标：无损清晰
            case THUMBNAIL:
                return 60; // 缩略图：体积优先
            case SCREENSHOT:
                return 85; // 截图：保留细节
            default:
                return 75;
        }
    }
    
    enum ImageType {
        PHOTO, ICON, THUMBNAIL, SCREENSHOT
    }
}

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public class InBitmapCompatibility {
    
    /**
     * 判断 Bitmap 是否可复用
     */
    public boolean canUseForInBitmap(Bitmap candidate, BitmapFactory.Options options) {
        if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.KITKAT) {
            // Android 4.4+ (API 19)
            // 只需满足内存大小条件
            int width = options.outWidth / options.inSampleSize;
            int height = options.outHeight / options.inSampleSize;
            int byteCount = width * height * getBytesPerPixel(options.inPreferredConfig);
            
            return candidate.getAllocationByteCount() >= byteCount;
            
        } else {
            // Android 4.3 及以下 (API 18-)
            // 必须严格匹配
            return candidate.getWidth() == options.outWidth
                && candidate.getHeight() == options.outHeight
                && options.inSampleSize == 1;
        }
    }
    
    private int getBytesPerPixel(Bitmap.Config config) {
        if (config == Bitmap.Config.ARGB_8888) {
            return 4;
        } else if (config == Bitmap.Config.RGB_565) {
            return 2;
        } else if (config == Bitmap.Config.ARGB_4444) {
            return 2; // 已废弃，实际使用 ARGB_8888
        } else if (config == Bitmap.Config.ALPHA_8) {
            return 1;
        }
        return 4; // 默认
    }
}

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public class InBitmapExample {
    
    private Set<SoftReference<Bitmap>> mReusableBitmaps = 
        Collections.synchronizedSet(new HashSet<>());
    
    /**
     * 解码时复用 Bitmap
     */
    public Bitmap decodeBitmapWithReuse(String path, int reqWidth, int reqHeight) {
        BitmapFactory.Options options = new BitmapFactory.Options();
        
        // 1. 第一次解码：获取尺寸
        options.inJustDecodeBounds = true;
        BitmapFactory.decodeFile(path, options);
        
        // 2. 计算采样率
        options.inSampleSize = calculateInSampleSize(options, reqWidth, reqHeight);
        
        // 3. 尝试找到可复用的 Bitmap
        options.inMutable = true; // 必须可变
        options.inBitmap = getBitmapFromReusableSet(options);
        options.inJustDecodeBounds = false;
        
        // 4. 解码
        try {
            Bitmap bitmap = BitmapFactory.decodeFile(path, options);
            return bitmap;
        } catch (IllegalArgumentException e) {
            // inBitmap 不可用，重试不复用
            options.inBitmap = null;
            return BitmapFactory.decodeFile(path, options);
        }
    }
    
    /**
     * 从复用池中查找合适的 Bitmap
     */
    private Bitmap getBitmapFromReusableSet(BitmapFactory.Options options) {
        Bitmap bitmap = null;
        
        if (!mReusableBitmaps.isEmpty()) {
            synchronized (mReusableBitmaps) {
                Iterator<SoftReference<Bitmap>> iterator = mReusableBitmaps.iterator();
                
                while (iterator.hasNext()) {
                    Bitmap item = iterator.next().get();
                    
                    if (item != null && item.isMutable()) {
                        if (canUseForInBitmap(item, options)) {
                            bitmap = item;
                            iterator.remove(); // 移除以避免重复使用
                            break;
                        }
                    } else {
                        iterator.remove(); // 清理已回收的引用
                    }
                }
            }
        }
        
        return bitmap;
    }
    
    /**
     * 将不再使用的 Bitmap 加入复用池
     */
    public void addBitmapToReusableSet(Bitmap bitmap) {
        if (bitmap != null && bitmap.isMutable()) {
            mReusableBitmaps.add(new SoftReference<>(bitmap));
        }
    }
}

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BitmapPool (接口)
    ├─ LruBitmapPool (LRU 策略)
    │   ├─ SizeStrategy (按大小分组)
    │   └─ AttributeStrategy (按属性分组)
    │
    └─ NoBitmapPool (空实现，禁用复用)

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public class LruBitmapPool implements BitmapPool {
    
    private final long maxSize; // 池最大容量
    private long currentSize;   // 当前已用容量
    
    private final LruPoolStrategy strategy; // 分组策略
    private final Set<Bitmap.Config> allowedConfigs; // 允许的格式
    
    public LruBitmapPool(long maxSize) {
        this.maxSize = maxSize;
        this.currentSize = 0;
        
        // Android 4.4+ 使用 SizeStrategy（仅按大小分组）
        // Android 4.3- 使用 AttributeStrategy（按尺寸+Config 分组）
        if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.KITKAT) {
            this.strategy = new SizeConfigStrategy();
        } else {
            this.strategy = new AttributeStrategy();
        }
        
        // 设置允许的配置
        this.allowedConfigs = new HashSet<>();
        allowedConfigs.add(Bitmap.Config.ARGB_8888);
        allowedConfigs.add(Bitmap.Config.RGB_565);
    }
    
    @Override
    public Bitmap get(int width, int height, Bitmap.Config config) {
        Bitmap result = getDirty(width, height, config);
        
        if (result != null) {
            // 清空像素数据（安全复用）
            result.eraseColor(Color.TRANSPARENT);
        }
        
        return result;
    }
    
    @Override
    public Bitmap getDirty(int width, int height, Bitmap.Config config) {
        // 1. 从策略中获取 Bitmap
        Bitmap result = strategy.get(width, height, config);
        
        if (result == null) {
            // 2. 池中无可用 Bitmap，创建新的
            result = Bitmap.createBitmap(width, height, config);
        } else {
            // 3. 更新容量统计
            currentSize -= strategy.getSize(result);
        }
        
        return result;
    }
    
    @Override
    public void put(Bitmap bitmap) {
        if (bitmap == null || !bitmap.isMutable() 
            || !allowedConfigs.contains(bitmap.getConfig())) {
            // 不符合条件，直接回收
            bitmap.recycle();
            return;
        }
        
        int size = strategy.getSize(bitmap);
        
        // 检查容量
        if (size >= maxSize) {
            bitmap.recycle();
            return;
        }
        
        // 添加到池中
        strategy.put(bitmap);
        currentSize += size;
        
        // 容量超限，移除旧 Bitmap
        evict();
    }
    
    /**
     * 驱逐策略：移除最少使用的 Bitmap
     */
    private void evict() {
        while (currentSize > maxSize) {
            Bitmap removed = strategy.removeLast();
            if (removed == null) {
                break;
            }
            
            currentSize -= strategy.getSize(removed);
            removed.recycle();
        }
    }
    
    @Override
    public void clearMemory() {
        evictAll();
    }
    
    @Override
    public void trimMemory(int level) {
        if (level >= ComponentCallbacks2.TRIM_MEMORY_MODERATE) {
            clearMemory();
        } else if (level >= ComponentCallbacks2.TRIM_MEMORY_BACKGROUND) {
            trimToSize(maxSize / 2);
        }
    }
    
    private void trimToSize(long targetSize) {
        while (currentSize > targetSize) {
            Bitmap removed = strategy.removeLast();
            if (removed == null) {
                break;
            }
            currentSize -= strategy.getSize(removed);
            removed.recycle();
        }
    }
    
    private void evictAll() {
        strategy.clear();
        currentSize = 0;
    }
}

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public class SizeConfigStrategy implements LruPoolStrategy {
    
    private final GroupedLinkedMap<Key, Bitmap> groupedMap = new GroupedLinkedMap<>();
    private final Map<Bitmap.Config, NavigableMap<Integer, Integer>> sortedSizes = new HashMap<>();
    
    @Override
    public void put(Bitmap bitmap) {
        int size = bitmap.getAllocationByteCount();
        Key key = keyPool.get(size, bitmap.getConfig());
        
        groupedMap.put(key, bitmap);
        
        // 记录此配置下的尺寸分布
        NavigableMap<Integer, Integer> sizes = getSizesForConfig(bitmap.getConfig());
        Integer current = sizes.get(size);
        sizes.put(size, current == null ? 1 : current + 1);
    }
    
    @Override
    public Bitmap get(int width, int height, Bitmap.Config config) {
        int size = width * height * getBytesPerPixel(config);
        Key key = keyPool.get(size, config);
        
        // 查找精确匹配
        Bitmap result = groupedMap.get(key);
        if (result != null) {
            return result;
        }
        
        // 查找更大的 Bitmap（允许浪费一定空间）
        NavigableMap<Integer, Integer> sizes = getSizesForConfig(config);
        Integer possibleSize = sizes.ceilingKey(size);
        
        if (possibleSize != null && possibleSize <= size * MAX_SIZE_MULTIPLE) {
            key = keyPool.get(possibleSize, config);
            result = groupedMap.get(key);
            
            if (result != null) {
                decrementSizeCount(possibleSize, config);
                return result;
            }
        }
        
        return null;
    }
    
    @Override
    public Bitmap removeLast() {
        Bitmap removed = groupedMap.removeLast();
        if (removed != null) {
            int size = removed.getAllocationByteCount();
            decrementSizeCount(size, removed.getConfig());
        }
        return removed;
    }
    
    private NavigableMap<Integer, Integer> getSizesForConfig(Bitmap.Config config) {
        NavigableMap<Integer, Integer> sizes = sortedSizes.get(config);
        if (sizes == null) {
            sizes = new TreeMap<>();
            sortedSizes.put(config, sizes);
        }
        return sizes;
    }
    
    private void decrementSizeCount(int size, Bitmap.Config config) {
        NavigableMap<Integer, Integer> sizes = getSizesForConfig(config);
        Integer current = sizes.get(size);
        
        if (current == 1) {
            sizes.remove(size);
        } else {
            sizes.put(size, current - 1);
        }
    }
    
    // 内部 Key 类
    private static class Key {
        private final KeyPool pool;
        private int size;
        private Bitmap.Config config;
        
        public Key(KeyPool pool) {
            this.pool = pool;
        }
        
        public void init(int size, Bitmap.Config config) {
            this.size = size;
            this.config = config;
        }
        
        @Override
        public boolean equals(Object o) {
            if (o instanceof Key) {
                Key other = (Key) o;
                return size == other.size && config == other.config;
            }
            return false;
        }
        
        @Override
        public int hashCode() {
            int result = size;
            result = 31 * result + (config != null ? config.hashCode() : 0);
            return result;
        }
    }
    
    // Key 对象池（避免频繁创建）
    private static class KeyPool {
        private final Queue<Key> pool = new ArrayDeque<>(MAX_SIZE);
        
        public Key get(int size, Bitmap.Config config) {
            Key key = pool.poll();
            if (key == null) {
                key = new Key(this);
            }
            key.init(size, config);
            return key;
        }
        
        public void offer(Key key) {
            if (pool.size() < MAX_SIZE) {
                pool.offer(key);
            }
        }
    }
}

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public class BitmapPoolBenchmark {
    
    public void benchmarkWithAndWithoutPool() {
        LruBitmapPool pool = new LruBitmapPool(20 * 1024 * 1024); // 20MB
        
        // 场景：连续加载 100 张图片
        String[] imagePaths = getImagePaths(100);
        
        // 1. 不使用复用池
        long startTime = System.nanoTime();
        for (String path : imagePaths) {
            Bitmap bitmap = BitmapFactory.decodeFile(path);
            // 使用 bitmap...
            bitmap.recycle();
        }
        long withoutPoolTime = (System.nanoTime() - startTime) / 1_000_000;
        
        // 2. 使用复用池
        startTime = System.nanoTime();
        for (String path : imagePaths) {
            BitmapFactory.Options options = new BitmapFactory.Options();
            options.inJustDecodeBounds = true;
            BitmapFactory.decodeFile(path, options);
            
            options.inMutable = true;
            options.inBitmap = pool.getDirty(
                options.outWidth, options.outHeight, Bitmap.Config.ARGB_8888
            );
            options.inJustDecodeBounds = false;
            
            Bitmap bitmap = BitmapFactory.decodeFile(path, options);
            // 使用 bitmap...
            pool.put(bitmap);
        }
        long withPoolTime = (System.nanoTime() - startTime) / 1_000_000;
        
        Log.d("Benchmark", "Without Pool: " + withoutPoolTime + "ms");
        Log.d("Benchmark", "With Pool: " + withPoolTime + "ms");
        Log.d("Benchmark", "Improvement: " + 
            String.format("%.1f%%", (withoutPoolTime - withPoolTime) * 100.0 / withoutPoolTime));
        
        // 典型结果：
        // Without Pool: 8500ms
        // With Pool: 5200ms
        // Improvement: 38.8%
    }
}

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public class MemoryChurnDetector {
    
    private long lastGCCount = 0;
    private long lastCheckTime = 0;
    
    /**
     * 检测内存抖动（频繁 GC）
     */
    public boolean detectChurn() {
        long currentTime = System.currentTimeMillis();
        long currentGCCount = Debug.getRuntimeStat("art.gc.gc-count");
        
        if (lastCheckTime > 0) {
            long timeDelta = currentTime - lastCheckTime;
            long gcDelta = currentGCCount - lastGCCount;
            
            // 1 秒内 GC 超过 3 次，认为存在抖动
            if (timeDelta < 1000 && gcDelta > 3) {
                Log.w("Memory", "Memory churn detected! " + 
                    gcDelta + " GCs in " + timeDelta + "ms");
                return true;
            }
        }
        
        lastGCCount = currentGCCount;
        lastCheckTime = currentTime;
        return false;
    }
}