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// 局部二值模式（LBP，纯 MoonBit）
///|
/// 基本局部二值模式（LBP）。对每个像素，与其 3x3 邻域的 8 个像素比较，
/// 大于等于中心记 1，否则记 0，按顺时针顺序组成 8 位二进制数。
/// 仅处理灰度图（channels=1）或 RGB 图（channels=3/4），alpha 通道不变。
pub fn lbp(img : @types.Image) -> @types.Image raise @types.LoadError {
// 输入验证
if img.width <= 0 || img.height <= 0 {
raise @types.LoadError::DecodeFailed("lbp: 图像尺寸必须大于0")
}
if img.channels != 1 && img.channels != 3 && img.channels != 4 {
raise @types.LoadError::DecodeFailed("lbp: 仅支持 channels=1/3/4")
}
let expected_size = img.width * img.height * img.channels
if img.data.length() != expected_size {
raise @types.LoadError::DecodeFailed(
"lbp: 数据大小不匹配，期望 " +
expected_size.to_string() +
"，实际 " +
img.data.length().to_string(),
)
}
let ch = img.channels
let color_ch = if ch >= 3 { 3 } else { 1 }
let w = img.width
let h = img.height
let n = w * h
let out : Array[Byte] = Array::make(n * ch, b'\x00')
// 预计算像素 Int 数组
let src : Array[Int] = Array::make(n * ch, 0)
for i in 0..<(n * ch) {
src[i] = img.data[i].to_int()
}
for c in 0..<color_ch {
// 内部区域：x in [1, w-1), y in [1, h-1)，直接访问 8 邻域
for y in 1..<(h - 1) {
for x in 1..<(w - 1) {
let center = src[(y * w + x) * ch + c]
let mut lbp_val = 0
// 左上、上、右上、右、右下、下、左下、左
if src[((y - 1) * w + (x - 1)) * ch + c] >= center {
lbp_val = lbp_val | 1
}
if src[((y - 1) * w + x) * ch + c] >= center {
lbp_val = lbp_val | 2
}
if src[((y - 1) * w + (x + 1)) * ch + c] >= center {
lbp_val = lbp_val | 4
}
if src[(y * w + (x + 1)) * ch + c] >= center {
lbp_val = lbp_val | 8
}
if src[((y + 1) * w + (x + 1)) * ch + c] >= center {
lbp_val = lbp_val | 16
}
if src[((y + 1) * w + x) * ch + c] >= center {
lbp_val = lbp_val | 32
}
if src[((y + 1) * w + (x - 1)) * ch + c] >= center {
lbp_val = lbp_val | 64
}
if src[(y * w + (x - 1)) * ch + c] >= center {
lbp_val = lbp_val | 128
}
out[(y * w + x) * ch + c] = lbp_val.to_byte()
}
}
// 边界区域：使用 get_pixel_safe
for y in 0..<h {
let y_inner = y >= 1 && y < h - 1
for x in 0..<w {
if y_inner && x >= 1 && x < w - 1 {
continue
}
let center = src[(y * w + x) * ch + c]
let mut lbp_val = 0
if get_pixel_safe(src, x - 1, y - 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 1
}
if get_pixel_safe(src, x, y - 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 2
}
if get_pixel_safe(src, x + 1, y - 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 4
}
if get_pixel_safe(src, x + 1, y, c, ch, w, h) >= center {
lbp_val = lbp_val | 8
}
if get_pixel_safe(src, x + 1, y + 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 16
}
if get_pixel_safe(src, x, y + 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 32
}
if get_pixel_safe(src, x - 1, y + 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 64
}
if get_pixel_safe(src, x - 1, y, c, ch, w, h) >= center {
lbp_val = lbp_val | 128
}
out[(y * w + x) * ch + c] = lbp_val.to_byte()
}
}
}
if ch == 4 {
for i in 0..<n {
out[i * 4 + 3] = img.data[i * 4 + 3]
}
}
@types.Image::{
width: w,
height: h,
channels: ch,
data: Bytes::from_array(out),
}
}
///|
/// 均匀局部二值模式（Uniform LBP）。
/// 均匀模式指 0→1 和 1→0 跳变次数 <= 2 的模式，共有 58 种均匀模式。
/// 非均匀模式统一映射为 59。输出范围 0~59。
pub fn lbp_uniform(img : @types.Image) -> @types.Image raise @types.LoadError {
// 输入验证
if img.width <= 0 || img.height <= 0 {
raise @types.LoadError::DecodeFailed(
"lbp_uniform: 图像尺寸必须大于0",
)
}
if img.channels != 1 && img.channels != 3 && img.channels != 4 {
raise @types.LoadError::DecodeFailed(
"lbp_uniform: 仅支持 channels=1/3/4",
)
}
let expected_size = img.width * img.height * img.channels
if img.data.length() != expected_size {
raise @types.LoadError::DecodeFailed(
"lbp_uniform: 数据大小不匹配，期望 " +
expected_size.to_string() +
"，实际 " +
img.data.length().to_string(),
)
}
let ch = img.channels
let color_ch = if ch >= 3 { 3 } else { 1 }
let w = img.width
let h = img.height
let n = w * h
let out : Array[Byte] = Array::make(n * ch, b'\x00')
// 预计算均匀模式映射表
let uniform_map = build_uniform_map()
// 预计算像素 Int 数组
let src : Array[Int] = Array::make(n * ch, 0)
for i in 0..<(n * ch) {
src[i] = img.data[i].to_int()
}
for c in 0..<color_ch {
// 内部区域
for y in 1..<(h - 1) {
for x in 1..<(w - 1) {
let center = src[(y * w + x) * ch + c]
let mut lbp_val = 0
if src[((y - 1) * w + (x - 1)) * ch + c] >= center {
lbp_val = lbp_val | 1
}
if src[((y - 1) * w + x) * ch + c] >= center {
lbp_val = lbp_val | 2
}
if src[((y - 1) * w + (x + 1)) * ch + c] >= center {
lbp_val = lbp_val | 4
}
if src[(y * w + (x + 1)) * ch + c] >= center {
lbp_val = lbp_val | 8
}
if src[((y + 1) * w + (x + 1)) * ch + c] >= center {
lbp_val = lbp_val | 16
}
if src[((y + 1) * w + x) * ch + c] >= center {
lbp_val = lbp_val | 32
}
if src[((y + 1) * w + (x - 1)) * ch + c] >= center {
lbp_val = lbp_val | 64
}
if src[(y * w + (x - 1)) * ch + c] >= center {
lbp_val = lbp_val | 128
}
out[(y * w + x) * ch + c] = uniform_map[lbp_val].to_byte()
}
}
// 边界区域
for y in 0..<h {
let y_inner = y >= 1 && y < h - 1
for x in 0..<w {
if y_inner && x >= 1 && x < w - 1 {
continue
}
let center = src[(y * w + x) * ch + c]
let mut lbp_val = 0
if get_pixel_safe(src, x - 1, y - 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 1
}
if get_pixel_safe(src, x, y - 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 2
}
if get_pixel_safe(src, x + 1, y - 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 4
}
if get_pixel_safe(src, x + 1, y, c, ch, w, h) >= center {
lbp_val = lbp_val | 8
}
if get_pixel_safe(src, x + 1, y + 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 16
}
if get_pixel_safe(src, x, y + 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 32
}
if get_pixel_safe(src, x - 1, y + 1, c, ch, w, h) >= center {
lbp_val = lbp_val | 64
}
if get_pixel_safe(src, x - 1, y, c, ch, w, h) >= center {
lbp_val = lbp_val | 128
}
out[(y * w + x) * ch + c] = uniform_map[lbp_val].to_byte()
}
}
}
if ch == 4 {
for i in 0..<n {
out[i * 4 + 3] = img.data[i * 4 + 3]
}
}
@types.Image::{
width: w,
height: h,
channels: ch,
data: Bytes::from_array(out),
}
}
///|
fn get_pixel_safe(
src : Array[Int],
x : Int,
y : Int,
c : Int,
ch : Int,
w : Int,
h : Int,
) -> Int {
if x < 0 || x >= w || y < 0 || y >= h {
return 0
}
src[(y * w + x) * ch + c]
}
///|
fn build_uniform_map() -> Array[Int] {
let map : Array[Int] = Array::make(256, 59)
let mut label = 0
for v in 0..<256 {
if count_transitions(v) <= 2 {
map[v] = label
label += 1
}
}
map
}
///|
fn count_transitions(v : Int) -> Int {
let mut count = 0
for i in 0..<8 {
let bit_i = (v >> i) & 1
let bit_next = (v >> ((i + 1) % 8)) & 1
if bit_i != bit_next {
count += 1
}
}
count
}