3D Rendering

Mitsuba – research-oriented rendering system

Mitsuba is an extensible rendering framework written in portable C++. It implements unbiased as well as biased techniques and contains heavy optimizations targeted towards current CPU architectures.

Mitsuba comes with a command-line interface as well as a graphical frontend to interactively explore scenes. While navigating, a rough preview is shown that becomes increasingly accurate as soon as all movements are stopped. Once a viewpoint has been chosen, a wide range of rendering techniques can be used to generate images, and their parameters can be tuned from within the program.

Mitsuba can transparently distribute work over a cluster without the need for a shared filesystem. Most implemented algorithms can be run in parallel over massive numbers of networked cores.

Features include:

  • Available rendering techniques:
    • Direct illumination.
    • Monte-Carlo path tracer which solves the full Radiative Transfer Equation.
    • Photon mapper with irradiance gradients.
    • Adjoint particle tracer.
    • Instant Radiosity (hardware-accelerated).
    • Progressive Photon Mapper.
    • Stochastic Progressive Photon Mapper.
    • Veach-style Bidirectional Path Tracer.
    • Kelemen-style Metropolis Light Transport.
    • Veach-style Metropolis Light Transport.
  • Supports the most commonly used scattering models: Lambertian surfaces, ideal dielectrics & mirrors as well as the the Phong & anisotropic Ward BRDFs.
  • Compute global illumination solutions in scenes containing large isotropic or anisotropic participating media.
  • Internally uses a O(n log n) SAH kd-tree compiler with support for primitive clipping (aka. perfect splits). The ray tracing core is built on Havran’s fast traversal algorithm.
  • Data exchange with the major modeling packages is supported using the COLLADA file format. Mitsuba can read DAE files and convert them into its native XML-based file format.
  • Spectral rendering, black body radiation and dispersion.
  • Customizable image reconstruction filters.
  • High dynamic-range input/output using the OpenEXR format.
  • Deterministic Quasi-Monte Carlo sampling.
  • Adaptive integration.
  • Depth of field.

Website: www.mitsuba-renderer.org
Support: Documentation
Developer: Wenzel Jakob
License: GNU General Public License v3.0

Mitsuba

Mitsuba is written in C++. Learn C++ with our recommended free books and free tutorials.

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