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Simulation and scientific computing
earth-observation
satellite imagery pipeline
Planet, Sentinel
System
Techniques · 4
Primitives · 23
earth-observation
Orthorectification
geometry · medium: Remove terrain and sensor distortion with a DEM and sensor model (RPC) to make map-accurate imagery
Radiometric calibration
media · medium: Convert sensor counts to reflectance: radiometric and atmospheric correction
Wavelet transform
signal-processing · medium: Discrete wavelet transforms (Haar, CDF 9/7 lifting) for compression and multiscale analysis
Chunked array storage
storage · medium: Cut an N-dimensional array into a regular grid of independently compressed blocks, so a slice read touches only the overlapping blocks and writers to different blocks run in parallel.
›
Map projections
geometry · low: Web Mercator, UTM and equal-area projections, datums and coordinate transforms
Object storage
cloud · low: S3-compatible blob storage at cents per GB-month with 11 nines durability; pick by egress price, request price and latency, not by storage price alone.
›
HTTP range requests
networking · low: Ask for byte offsets with Range and get a 206 slice back; the standard way to resume, seek and read big remote files piecewise.
›
Map tile pyramid
geometry · low: Z/x/y tile pyramids, quadkeys and overviews for multi-resolution maps and imagery
R-tree
geometry · low: A balanced tree of nested bounding boxes that indexes rectangles and points, answering window and nearest-neighbour queries by pruning whole subtrees.
›
Space filling curves
geometry · low: Z-order/Morton (geohash) and Hilbert curves mapping multi-dimensional points to sortable keys
Image resampling filters
graphics · low: Resize an image by convolving with a kernel (box, triangle, cubic, Lanczos) whose width scales with the shrink factor, done as two separable 1-D passes with precomputed weights.
›
Convolutional networks
ml-training · low: Layers that slide a small shared kernel over a grid, giving translation equivariance and few parameters; still the most compute-efficient choice for many vision tasks.
›
Fast Fourier transform
numerics · low: Computes the DFT in O(n log n) by recursively splitting into even and odd halves; the basis of fast convolution and spectral methods.
›
Image warping remap
graphics · low: Resampling with lookup maps: resize, lens undistortion, homographies, bilinear/bicubic
Lens distortion correction
graphics · low: Pre-warp rendered frames for headset optics: barrel distortion mesh and chromatic aberration
Newton root finding
numerics · low: Linearize at the guess and jump to the tangent root; quadratic convergence near a simple root, made robust by brackets (1D) or line search.
›
Spline interpolation
numerics · low: Linear, bilinear/trilinear and cubic spline interpolation on grids and tables
Robust statistics
statistics · low: Location and scale estimates (median, MAD, trimmed mean, Huber M-estimator) that stay correct when a minority of the data is garbage.
›
SIMD programming
hardware-os · low: Process 4-16 lanes per instruction with AVX2, AVX-512 or NEON via Rust std::arch, with runtime dispatch and a portable fallback.
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IIR and FIR filters
signal-processing · low: Two ways to shape a sampled signal's spectrum: FIR (finite taps, always stable, exact linear phase) or IIR (feedback, a few coefficients, cheap but phase-distorting).
›
+ 7 more primitives
System
Techniques · 4
Primitives · 23
earth-observation
Orthorectification
geometry · medium: Remove terrain and sensor distortion with a DEM and sensor model (RPC) to make map-accurate imagery
Radiometric calibration
media · medium: Convert sensor counts to reflectance: radiometric and atmospheric correction
Wavelet transform
signal-processing · medium: Discrete wavelet transforms (Haar, CDF 9/7 lifting) for compression and multiscale analysis
Chunked array storage
storage · medium: Cut an N-dimensional array into a regular grid of independently compressed blocks, so a slice read touches only the overlapping blocks and writers to different blocks run in parallel.
›
Map projections
geometry · low: Web Mercator, UTM and equal-area projections, datums and coordinate transforms
Object storage
cloud · low: S3-compatible blob storage at cents per GB-month with 11 nines durability; pick by egress price, request price and latency, not by storage price alone.
›
HTTP range requests
networking · low: Ask for byte offsets with Range and get a 206 slice back; the standard way to resume, seek and read big remote files piecewise.
›
Map tile pyramid
geometry · low: Z/x/y tile pyramids, quadkeys and overviews for multi-resolution maps and imagery
R-tree
geometry · low: A balanced tree of nested bounding boxes that indexes rectangles and points, answering window and nearest-neighbour queries by pruning whole subtrees.
›
Space filling curves
geometry · low: Z-order/Morton (geohash) and Hilbert curves mapping multi-dimensional points to sortable keys
Image resampling filters
graphics · low: Resize an image by convolving with a kernel (box, triangle, cubic, Lanczos) whose width scales with the shrink factor, done as two separable 1-D passes with precomputed weights.
›
Convolutional networks
ml-training · low: Layers that slide a small shared kernel over a grid, giving translation equivariance and few parameters; still the most compute-efficient choice for many vision tasks.
›
Fast Fourier transform
numerics · low: Computes the DFT in O(n log n) by recursively splitting into even and odd halves; the basis of fast convolution and spectral methods.
›
Image warping remap
graphics · low: Resampling with lookup maps: resize, lens undistortion, homographies, bilinear/bicubic
Lens distortion correction
graphics · low: Pre-warp rendered frames for headset optics: barrel distortion mesh and chromatic aberration
Newton root finding
numerics · low: Linearize at the guess and jump to the tangent root; quadratic convergence near a simple root, made robust by brackets (1D) or line search.
›
Spline interpolation
numerics · low: Linear, bilinear/trilinear and cubic spline interpolation on grids and tables
Robust statistics
statistics · low: Location and scale estimates (median, MAD, trimmed mean, Huber M-estimator) that stay correct when a minority of the data is garbage.
›
SIMD programming
hardware-os · low: Process 4-16 lanes per instruction with AVX2, AVX-512 or NEON via Rust std::arch, with runtime dispatch and a portable fallback.
›
IIR and FIR filters
signal-processing · low: Two ways to shape a sampled signal's spectrum: FIR (finite taps, always stable, exact linear phase) or IIR (feedback, a few coefficients, cheap but phase-distorting).
›
Delta encoding
compression · low: Store differences between consecutive values instead of the values, turning sorted IDs, timestamps and counters into small numbers that pack into few bits.
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Zstandard (zstd)
compression · low: LZ77 plus Huffman and FSE entropy coding, with levels from LZ4-like speed to xz-like ratio, all decoding at about 1-2 GB/s.
›
Bit packing and PFOR
compression · low: Store blocks of integers with exactly b bits each and patch rare outliers separately (PFOR); the fastest integer codec family, billions of values per second.
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Varint (LEB128)
compression · low: Variable-length integers in 7-bit groups with a continuation bit; small numbers take 1 byte, the wire format of Protobuf, WebAssembly and DWARF.
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Convolution image filters
graphics · low: Separable 2D convolution kernels for blur, sharpen (unsharp mask) and edges with border handling
LU and Cholesky factorization
numerics · low: Factor A = PLU (any square matrix, partial pivoting) or A = LLᵀ (SPD) once in O(n³), then solve each right-hand side in O(n²).
›
Biquad filters
signal-processing · low: Second-order IIR sections (RBJ cookbook): low/high pass, peaking EQ; stable cascades
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