  Recently, a non-classical eigenvalue solver, called RIM, was proposed to
compute (all) eigenvalues in a region on the complex plane. Without solving any
eigenvalue problem, it tests if a region contains eigenvalues using an
approximate spectral projection. Regions that contain eigenvalues are
subdivided and tested recursively until eigenvalues are isolated with a
specified precision. This makes RIM an eigensolver distinct from all existing
methods. Furthermore, it requires no a priori spectral information. In this
paper, we propose an improved version of {\bf RIM} for non-Hermitian eigenvalue
problems. Using Cayley transformation and Arnoldi's method, the computation
cost is reduced significantly. Effectiveness and efficiency of the new method
are demonstrated by numerical examples and compared with 'eigs' in Matlab.
