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// 色调映射（纯 MoonBit）：Reinhard + Gamma
// 将 HDR float 图像 (ImageF) 映射到 LDR 8-bit 图像 (Image)
///|
fn read_float_le(data : Bytes, offset : Int) -> Float {
let b0 = data[offset].to_int()
let b1 = data[offset + 1].to_int()
let b2 = data[offset + 2].to_int()
let b3 = data[offset + 3].to_int()
let bits = b0 | (b1 << 8) | (b2 << 16) | (b3 << 24)
Float::reinterpret_from_int(bits)
}
///|
fn log_f(x : Float) -> Float {
Float::from_double(@math.log2(x.to_double()) * 0.6931471805599453)
}
///|
/// Reinhard 全局色调映射。
/// key 控制整体亮度（默认 0.18），值越大越亮。
/// 公式：L_out = L_scaled / (1 + L_scaled)，其中 L_scaled = key * L / L_avg。
pub fn reinhard_tonemap(
imgf : @types.ImageF,
key? : Float = 0.18F,
) -> @types.Image raise @types.LoadError {
// 输入验证
if imgf.width <= 0 || imgf.height <= 0 {
raise @types.LoadError::DecodeFailed(
"reinhard_tonemap: 图像尺寸必须大于0",
)
}
if imgf.channels < 1 || imgf.channels > 4 {
raise @types.LoadError::DecodeFailed(
"reinhard_tonemap: 通道数必须在1-4之间",
)
}
let expected_size = imgf.width * imgf.height * imgf.channels * 4
if imgf.data.length() != expected_size {
raise @types.LoadError::DecodeFailed(
"reinhard_tonemap: 数据大小不匹配，期望 " +
expected_size.to_string() +
"，实际 " +
imgf.data.length().to_string(),
)
}
if key <= 0.0F {
raise @types.LoadError::DecodeFailed("reinhard_tonemap: key必须大于0")
}
let w = imgf.width
let h = imgf.height
let ch = imgf.channels
let n = w * h
let color_ch = if ch >= 3 { 3 } else { ch }
// 计算对数平均亮度
let mut log_sum = 0.0F
for i in 0..<n {
let r = read_float_le(imgf.data, i * ch * 4)
let g = read_float_le(imgf.data, i * ch * 4 + 4)
let b = read_float_le(imgf.data, i * ch * 4 + 8)
let lum = 0.2126F * r + 0.7152F * g + 0.0722F * b
let lum_safe = if lum > 0.0F { lum } else { 0.0001F }
log_sum += log_f(lum_safe)
}
let log_avg = @math.expf(log_sum / Float::from_int(n))
let scale = key / log_avg
// 应用 Reinhard 映射
let out : Array[Byte] = Array::make(n * ch, b'\x00')
for i in 0..<n {
for c in 0..<color_ch {
let v = read_float_le(imgf.data, (i * ch + c) * 4)
let scaled = v * scale
let mapped = scaled / (1.0F + scaled)
let val = (mapped * 255.0F + 0.5F).to_int().clamp(min=0, max=255)
out[i * ch + c] = val.to_byte()
}
if ch == 4 {
out[i * ch + 3] = b'\xFF'
}
}
@types.Image::{
width: w,
height: h,
channels: ch,
data: Bytes::from_array(out),
}
}
///|
/// Gamma 色调映射。
/// 先归一化到 [0,1]，再应用 gamma 校正：L_out = L^(1/gamma)。
/// gamma > 1 提亮暗部，gamma < 1 压暗。
pub fn gamma_tonemap(
imgf : @types.ImageF,
gamma : Float,
) -> @types.Image raise @types.LoadError {
// 输入验证
if imgf.width <= 0 || imgf.height <= 0 {
raise @types.LoadError::DecodeFailed(
"gamma_tonemap: 图像尺寸必须大于0",
)
}
if imgf.channels < 1 || imgf.channels > 4 {
raise @types.LoadError::DecodeFailed(
"gamma_tonemap: 通道数必须在1-4之间",
)
}
let expected_size = imgf.width * imgf.height * imgf.channels * 4
if imgf.data.length() != expected_size {
raise @types.LoadError::DecodeFailed(
"gamma_tonemap: 数据大小不匹配，期望 " +
expected_size.to_string() +
"，实际 " +
imgf.data.length().to_string(),
)
}
if gamma <= 0.0F {
raise @types.LoadError::DecodeFailed("gamma_tonemap: gamma必须大于0")
}
let w = imgf.width
let h = imgf.height
let ch = imgf.channels
let n = w * h
let color_ch = if ch >= 3 { 3 } else { ch }
// 找最大值用于归一化
let mut max_val = 0.0F
for i in 0..<n {
for c in 0..<color_ch {
let v = read_float_le(imgf.data, (i * ch + c) * 4)
if v > max_val {
max_val = v
}
}
}
if max_val <= 0.0F {
return @types.Image::{
width: w,
height: h,
channels: ch,
data: Bytes::from_array(Array::make(n * ch, b'\x00')),
}
}
let inv_gamma = 1.0F / gamma
let out : Array[Byte] = Array::make(n * ch, b'\x00')
for i in 0..<n {
for c in 0..<color_ch {
let v = read_float_le(imgf.data, (i * ch + c) * 4)
let normalized = v / max_val
let mapped = if normalized > 0.0F {
@math.powf(normalized, inv_gamma)
} else {
0.0F
}
let val = (mapped * 255.0F + 0.5F).to_int().clamp(min=0, max=255)
out[i * ch + c] = val.to_byte()
}
if ch == 4 {
out[i * ch + 3] = b'\xFF'
}
}
@types.Image::{
width: w,
height: h,
channels: ch,
data: Bytes::from_array(out),
}
}