Lattice approximations for partial differential equations describing physical phenomena are commonly used for the numerical simulation of many problems otherwise intractable by pure analytical approaches. The discretization inevitably leads to many of the original symmetries to be broken or modified. In the case of Maxwell's equations for example, invariance and isotropy of the speed of light in vacuum is invariably lost because of the so-called grid dispersion. Since it is a cumulative effect, grid dispersion is particularly harmful for the accuracy of results of large-scale simulations of scattering problems. Grid dispersion is usually combated by either increasing the lattice resolution or by employing higher-order schemes with larger stencils for the space and time derivatives. Both alternatives lead to increased computational cost to simulate a problem of a given physical size. Here, we introduce a general approach to develop lattice approximations with reduced grid dispersion error for a given stencil (and hence at no additional computational cost). The present approach is based on first obtaining stencil coefficients in the Fourier domain that minimize the maximum grid dispersion error for wave propagation at all directions (minimax sense). The resulting coefficients are then expanded into a Taylor series in terms of the frequency variable and incorporated into time-domain (update) equations after an inverse Fourier transformation. Maximally flat (Butterworth) or Chebyshev filters are subsequently used to minimize the wave speed variations for a given frequency range of interest. The use of such filters also allows for the adjustment of the grid dispersion characteristics so as to minimize not only the local dispersion error but also the accumulated phase error in a frequency range of interest.